bluuebunny/crossref_metadata_2025 huggingface dataset:
(Invited) Multifunctional Membrane Coated Electrocatalysts
Authors: Labrador Natalie Yumiko , Esposito Daniel V
Published: January 2022

Electrocatalysts are essential components in many emerging electrochemical technologies due to their ability to efficiently facilitate the interconversion between electrical and chemical energy. However, significant improvements in the stability, activity, and selectivity of state-of-the-art electrocatalysts must be made if these technologies are going to play a major role in a sustainable energy future. The vast majority of electrocatalysts used in today’s commercial devices are comprised of metallic nanoparticles or thin films that are deposited onto a conductive support and partially exposed to the bulk electrolyte. By contrast, this work has explored an alternate electrocatalyst architecture in which the active electrocatalyst has been encapsulated by an ultrathin permeable overlayer. Specifically, we encapsulate Pt nanoparticle and thin film electrocatalysts with 2-20 nm thick layers of silicon oxide (SiOx) fabricated using a room temperature deposition process.[1] Through a combination of physical characterization and electroanalytical measurements, we show that these permeable overlayers can serve as nano-scale membranes that provide significant benefits for stabilizing Pt nanoparticles and imparting advanced catalytic functionalities such as poison-resistance. This work has focused on SiOx-encapsulated Pt thin films electrocatalysts for the hydrogen evolution reaction, but the membrane coated electrocatalyst architecture also has great potential as a tunable platform that can be extended to many other materials and chemistries.

[1] N. Y. Labrador, X. Li, Y. Liu, J. T. Koberstein, R. Wang, H. Tan, T. P. Moffat, and D. V. Esposito, Nano Letters, 16, 6452-6459, 2016.
Noble-Metal-Free Photocatalytic Hydrogen Evolution Activity:Defect Engineering in TiO2 Nanotubes
Authors: Zhou Xuemei , Schmuki Patrik
Published: January 2022

The use of TiO2 photoelectrodes (or TiO2 suspensions) to produce hydrogen from various electrolytes (with or without sacrificial agents) has been highly investigated over the past decades and still remains a most investigated topic.1 The advantage of anodic TiO2 nanotubes (NTs) is not only that they provide a one dimensional charge-transfer path, but also they are back-contacted on metal substrate that can be used as electrodes directly.2 Pathways to create noble-metal-free H2 evolution activity on TiO2 NTs are not only of considerable scientific but also of high economic interest.3-4 Here we introduce an efficient way to introduce a sub-surface configuration of a broad range of lattice defects (namely vacancy/interstitial pairs) using high energy ion implantation.5

In this study, we report defect containing TiO2 NTs that strongly acts as photo co-catalysts. This catalyst is obtained by low-dose nitrogen ion-implantation that can be tuned to obtain a highly defined ion and defect distribution within the TiO2 NT substrate. A particular advantage of creating these defect centers by N-implantation is that the active centers can be placed as a coherent layer at a defined sub-surface location and allow surface patterning.6 The catalysts presented here show considerable photocatalytic activity for hydrogen evolution under solar light illumination in the absence of noble metal or external bias. These results provide a new platform for TiO2 based photo co-catalysts.

References

Fujishima and K. Honda, Nature, 1972, 238, 37-38.

X. Zhou, N. T. Nguyen, S. Özkan, P. Schmuki, Electrochem. Comm., 2014(46,) 157–162.

Zhou, N. Liu and P. Schmuki, Electrochem. Commun., 2014 (49), 60–64.

N Liu, V. Häublein, X. Zhou, U. Venkatesan, M. Hartmann, M. Mačković, T. Nakajima, E. Spiecker, A. Osvet, L. Frey, and P. Schmuki, Nano Lett., 2015, 15 (10), 6815–6820.

Zhou, V. Häublein, N. Liu, N. T. Nguyen, E. M. Zolnhofer, H. Tsuchiya, M. S. Killian, K. Meyer, L. Frey, P. Schmuki, Angew. Chem. Int. Ed. 2016, 55, 3763-3767.

X. Zhou, N. Liu, P. Schmuki, ACS Cat., 2017, 7, 3210–3235.
Best Proximity Points of Multivalued Hardy‐Roger’s Type (Cyclic) Contractive Mappings of b‐Metric Spaces
Authors: Ali Basit , Khan Arshad Ali , Hussain Azhar
Published: January 2022

In this article, we introduce a new type of generalized multivalued Hardy and Roger’s type proximal contractive and proximal cyclic contractive mappings of b‐metric spaces and develop some results for the existence of best proximity point(s). Moreover, we obtain some results for the existence and uniqueness of best proximity points for single‐valued mappings. Examples are given to explain the main results.
PrACTiC: A Predictive Algorithm for Chemoradiotherapy-Induced Cytopenia in Glioblastoma Patients
Authors: Amouheidari Alireza , Alirezaei Zahra , Rauh Stefan , Hassanpour Masoud
Published: January 2022

Background. Chemotherapy-induced cytopenia is the most frequent side effect of chemoradiotherapy in glioblastoma patients which may lead to reduced delivery of treatment. This study aims to develop a predictive model that is able to forecast the cytopenia induced by temozolomide (TMZ) during concomitant chemoradiotherapy. Methods. Medical records of 128 patients with newly diagnosed glioblastoma were evaluated to extract the baseline complete blood test before and during the six weeks of chemoradiotherapy to create a dataset for the development of ML models. Using the constructed dataset, different ML algorithms were trained and tested. Results. Our proposed algorithm achieved accuracies of 85.6%, 88.7%, and 89.3% in predicting thrombocytopenia, lymphopenia, and neutropenia, respectively. Conclusions. The algorithm designed and developed in this study, called PrACTiC, showed promising results in the accurate prediction of thrombocytopenia, neutropenia, and lymphopenia induced by TMZ in glioblastoma patients. PrACTiC can provide valuable insight for physicians and help them to make the necessary treatment modifications and prevent the toxicities.
Data Feature Extraction Method of Wearable Sensor Based on Convolutional Neural Network
Authors: Wang Baoying
Published: January 2022

With the rapid development of society and science technology, human health issues have attracted much attention due to wearable devices’ ability to provide high-quality sports, health, and activity monitoring services. This paper proposes a method for feature extraction of wearable sensor data based on a convolutional neural network (CNN). First, it uses the Kalman filter to fuse the data to obtain a preliminary state estimation, and then it uses CNN to recognize human behavior, thereby obtaining the corresponding behavior set. Moreover, this paper conducts experiments on 5 datasets. The experimental results show that the method in this paper extracts data features at multiple scales while fully maintaining data independence, can effectively extract corresponding feature data, and has strong generalization ability, which can adapt to different learning tasks.
Network Pharmacology-Based Analysis on Lonicera japonica for Chronic Osteomyelitis Treatment
Authors: Shao Tingting , Huang Kai
Published: January 2022

Ethnopharmacological Relevance. Lonicera japonica (LJP) is a broadly used traditional Chinese medication treatment for chronic osteomyelitis (COM). But, the main antiosteomyelitis compounds and functional targets of LJP are still unclear. Aim of the Study. To screen LJP drug targets and active compounds in COM treatment. Materials and Methods. Active compounds of LJP were examined established on the analysis platform, Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. DrugBank identified drug targets and annotated them on UniPort and GeneCards. Besides, the COM-related genes were identified on GeneCards. The network of the drug, main active compounds, targets, and diseases was built utilizing Cytoscape. STRING was utilized to build the protein-protein interaction network. Moreover, the KEGG and GO pathway enrichment analysis were applied to analyze biological function. Results. 23 active compounds of LJP were screened, and 204 drug targets and 686 COM-related genes were identified. Forty-five intersection genes were overlapped from 204 drug targets and 686 COM-related genes. The drug-active compounds-target protein-diseases network was established based on 23 active compounds of LJP and 45 intersection genes. Moreover, the interaction of 45 intersection genes was explored by the PPI network, and the drug-active compounds-target protein-diseases network was formed grounded by 23 active compounds of LJP, 45 intersection genes, and PPI network. The KEGG and GO pathway enrichment analysis specified that 45 intersection genes primarily enriched in immune-related pathways and oxidative stress-related pathways. Conclusions. In the research done, the main active compounds of LJP and drug targets in the treatment of COM were identified. Our findings might provide the ingredient option of LJP and drug targets of LJP in COM treatment.
Application of Internet of Things on the Healthcare Field Using Convolutional Neural Network Processing
Authors: Mohana J. , Yakkala Bhaskarrao , Vimalnath S. , Benson Mansingh P. M. , Yuvaraj N. , Srihari K. , Sasikala G. , Mahalakshmi V. , Yasir Abdullah R. , Sundramurthy Venkatesa Prabhu
Published: January 2022

Population at risk can benefit greatly from remote health monitoring because it allows for early detection and treatment. Because of recent advances in Internet-of-Things (IoT) paradigms, such monitoring systems are now available everywhere. Due to the essential nature of the patients being monitored, these systems demand a high level of quality in aspects such as availability and accuracy. In health applications, where a lot of data are accessible, deep learning algorithms have the potential to perform well. In this paper, we develop a deep learning architecture called the convolutional neural network (CNN), which we examine in this study to see if it can be implemented. The study uses the IoT system with a centralised cloud server, where it is considered as an ideal input data acquisition module. The study uses cloud computing resources by distributing CNN operations to the servers with outsourced fitness functions to be performed at the edge. The results of the simulation show that the proposed method achieves a higher rate of classifying the input instances from the data acquisition tools than other methods. From the results, it is seen that the proposed CNN achieves an average accurate rate of 99.6% on training datasets and 86.3% on testing datasets.
Dynamic Invariant-Specific Representation Fusion Network for Multimodal Sentiment Analysis
Authors: He Jing , Yanga Haonan , Zhang Changfan , Chen Hongrun , Xua Yifu
Published: January 2022

Multimodal sentiment analysis (MSA) aims to infer emotions from linguistic, auditory, and visual sequences. Multimodal information representation method and fusion technology are keys to MSA. However, the problem of difficulty in fully obtaining heterogeneous data interactions in MSA usually exists. To solve these problems, a new framework, namely, dynamic invariant-specific representation fusion network (DISRFN), is put forward in this study. Firstly, in order to effectively utilize redundant information, the joint domain separation representations of all modes are obtained through the improved joint domain separation network. Then, the hierarchical graph fusion net (HGFN) is used for dynamically fusing each representation to obtain the interaction of multimodal data for guidance in the sentiment analysis. Moreover, comparative experiments are performed on popular MSA data sets MOSI and MOSEI, and the research on fusion strategy, loss function ablation, and similarity loss function analysis experiments is designed. The experimental results verify the effectiveness of the DISRFN framework and loss function.
Analysis on Value of Applying Serum miR-144 and miR-221 Levels in Diagnosing Atherosclerosis
Authors: Zhang Jianxiu , Cao Qian , Zhang Zhenying , Du Chenguang , Wang Lizhong
Published: January 2022

Objective. To explore the value of serum miR-144 and miR-221 in diagnosing atherosclerosis (AS). Methods. The clinical data of 52 AS patients treated in the department of cardiovascular medicine of our hospital from August 2019 to August 2020 were retrospectively analyzed, and 53 healthy persons were selected from the physical examination center at the same period as the control group. By measuring the indicators including the serum vascular endothelial growth factor (VEGF), superoxide dismutase (SOD), miR-144, and miR-221 in patients of both groups, their value of diagnosing AS was analyzed. Results. Compared with the control group, the AS group obtained significantly higher serum miR-221 and miR-144 expression levels (

P
<
0.001

), significantly higher mean serum homocysteine (Hcy) level value (

P
<
0.001

), lower mean serum SOD level (

P
<
0.001

), and significantly higher level values of serum VEGF, nuclear factor-kappaB (NF-kB), and transforming growth factor-β (TGF-β) (

P
<
0.001

), and the area under ROC curve, sensitivity, and specificity of combining miR-221 with miR-144 were significantly higher than those of single diagnosis. Conclusion. Serum miR-221 and miR-144 expression levels are increased in AS patients, and combining the two indicators in diagnosis is more accurate and can provide an accurate basis for diagnosis and condition assessment of AS.
Short-Term Solar Irradiance Prediction Based on Multichannel LSTM Neural Networks Using Edge-Based IoT System
Authors: Pi Maozheng , Jin Ning , Chen Dongxiao , Lou Bing
Published: January 2022

Most photovoltaic power generation methods use global level irradiance (GHI) as the main input and output. However, randomness, instability, and intermittency are the main factors that seriously degrade the solar irradiance prediction results. Traditional data-driven prediction models are difficult for accurate predictions. In this study, a multichannel deep learning model named multichannel, wavelet transform combining convolutional neural network and bidirectional long short-term memory (MC-WT-CBiLSTM) framework-based edge computing and IoT system is proposed to improve the GHI prediction accuracy. The solar irradiance data is decomposed by wavelet transform to reduce data complexity. Each decomposed component is inputted into the multichannel MC-CBiLSTM deep learning framework for forecasting and combined to produce the final results. The comparison with existing solar irradiance forecasting methods shows that the proposed MC-WT-CBiLSTM deep learning framework has obvious advantages in the prediction of various time horizons.
Exosomal miR-17-3p Alleviates Programmed Necrosis in Cardiac Ischemia/Reperfusion Injury by Regulating TIMP3 Expression
Authors: Liu Zhuyuan , Zhu Didi , Yu Fuchao , Yang Mingming , Huang Dan , Ji Zhenjun , Lu Wenbin , Ma Genshan
Published: January 2022

Objective. Myocardial ischemia/reperfusion (I/R) injury can aggravate myocardial injury. Programmed necrosis plays a crucial role in this injury. However, the role of exosomal miRNAs in myocardial I/R injury remains unclear. Therefore, this study is aimed at exploring the function and mechanism of exosomal miR-17-3p in myocardial I/R injury. Methods. The myocardial I/R injury animal model was established in C57BL/6 mice. Exosomes were identified using transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA), and Western blotting. Programmed necrosis was detected by PI staining. Heart function and myocardial infarct size were evaluated using echocardiography and triphenyl tetrazolium chloride (TTC) staining, respectively. Histopathological changes were visualized by hematoxylin and eosin (H&E) and Masson staining. The regulation of TIMP3 expression by miR-17-3p was verified using a dual-luciferase reporter assay. Lactate dehydrogenase (LDH) and tumor necrosis factor-α (TNF-α) levels were measured by enzyme-linked immunosorbent assays (ELISA). TIMP3 expression was measured by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and Western blotting. Results. We demonstrated that miR-17-3p was significantly downregulated in peripheral blood exosomes after cardiac I/R injury. Further analysis indicated that exosomal miR-17-3p attenuated H2O2-induced programmed necrosis in cardiomyocytes in vitro. Moreover, TIMP3 was a target for miR-17-3p. TIMP3 affected H2O2-induced programmed necrosis in cardiomyocytes. This effect was modulated by miR-17-3p in vitro. Furthermore, exosomal miR-17-3p greatly alleviated cardiac I/R injury in vivo. Conclusions. The present study demonstrated that exosomal miR-17-3p alleviated the programmed necrosis associated with cardiac I/R injury by regulating TIMP3 expression. These findings could represent a potential treatment for I/R injury.
Role and Mechanism of the Renin-Angiotensin-Aldosterone System in the Onset and Development of Cardiorenal Syndrome
Authors: Ma Kexin , Gao Weifang , Xu Huazhou , Liang Wenjie , Ma Guoping
Published: January 2022

Cardiorenal syndrome (CRS), a clinical syndrome involving multiple pathological mechanisms, exhibits high morbidity and mortality. According to the primary activity of the disease, CRS can be divided into cardiorenal syndrome (type I and type II), renal heart syndrome (type III and type IV), and secondary heart and kidney disease (type V). The renin-angiotensin-aldosterone system (RAAS) is an important humoral regulatory system of the body that exists widely in various tissues and organs. As a compensatory mechanism, the RAAS is typically activated to participate in the regulation of target organ function. RAAS activation plays a key role in the pathogenesis of CRS. The RAAS induces the onset and development of CRS by mediating oxidative stress, uremic toxin overload, and asymmetric dimethylarginine production. Research on the mechanism of RAAS-induced CRS can provide multiple intervention methods that are of great significance for reducing end-stage organ damage and further improving the quality of life of patients with CRS.
Construction of Prediction Model of Deep Vein Thrombosis Risk after Total Knee Arthroplasty Based on XGBoost Algorithm
Authors: Chen Yuhuan , Jiang Yingqing
Published: January 2022

Objective. Based on the XGBoost algorithm, the prediction model of the risk of deep vein thrombosis (DVT) in patients after total knee arthroplasty (TKA) was established, and the prediction performance was compared. Methods. A total of 100 patients with TKA from January 2019 to December 2020 were retrospectively selected as the study subjects and randomly divided into a training set (

n
=
60

) and a test set (

n
=
40

). The training set data was used to construct the XGBoost algorithm prediction model and to screen the predictive factors of postoperative DVT in TKA patients. The prediction effect of the model was evaluated by using the test set data. An independent sample

T

-test was used for comparison between groups, and the

χ

2

test was used for comparison between counting data groups. Results. The top five items were combined with multiple injuries (35 points), time from injury to operation (28 points), age (24 points), combined with coronary heart disease (21 points), and D-dimer 1 day after operation (16 points). In the training set, the area under the curve of the XGBoost algorithm model was 0.832 (95% CI: 0.748-0.916). Conclusion. The model based on the XGBoost algorithm can predict the incidence of DVT in patients after TKA with good performance.
Effect of Eel Cookie Supplementation on the Hemoglobin Status of Pregnant Women with Anaemia: A Pilot Study
Authors: Herawati Dewi Marhaeni Diah , Sunjaya Deni Kurniadi , Janah Lailia Fathul , Arisanti Nita , Susiarno Hadi
Published: January 2022

Background. Anaemia in pregnancy is a major global health problem. Iron and folic acid (IFAS) and animal-based supplement consumption could improve the hemoglobin status of pregnant women. This study is aimed at determining the effect of eel cookie supplementation on hemoglobin levels of pregnant women. Methods. This pilot study with pretest–posttest design was conducted in Tamanjaya Public Health Center, Geopark Ciletuh, Sukabumi District, West Java Province, Indonesia. A total of 40 voluntary pregnant women were divided into two groups: an intervention group that received 11 pieces of eel cookies and control group that received the same number of cookies without eel. The women’s hemoglobin level was analysed using

t

-test, Mann-Whitney, Wilcoxon, and analysis of covariance tests. Results. After consuming the eel cookies for 1 month, there was a significantly greater increase in the hemoglobin levels in the intervention group than those in the control group, which were 1.69 and 0.69 g/dL, respectively. Improvement in percentage of mean hemoglobin was higher in the intervention group than in the control group, which was 17.21% and 6.53%, respectively. Conclusions. Supplementation with eel cookies and IFAS for 1 month could improve the hemoglobin status in pregnant women with anaemia.
The Retrievability of Calcium Silicate-Based Sealer during Retreatment and the Effectiveness of Additional Passive Ultrasonic Irrigation: A Microcomputed Tomographic Study
Authors: Lee TaeYeon , Kahm Se Hoon , Kim KyungJae , Yang SungEun
Published: January 2022

This study investigated the retreatability of EndoSeal MTA (Maruch, Wonju, Korea) according to the presence or absence of a canal isthmus and the additional use of passive ultrasonic irrigation (PUI) through microcomputed tomography (micro-CT) imaging. An epoxy resin sealer (AH Plus (Dentsply DeTrey, Konstanz, Germany)) was used as a reference for comparison. Forty-five artificial mandibular molars (TRUETOOTH #19, DELABS, Santa Barbara, CA) with a mesial canal with an isthmus and a distal canal without an isthmus were obturated using gutta-percha and one of the following sealers (

n
=
15

each): AH Plus, EndoSeal MTA, and EndoSeal MTA + PUI. Micro-CT scanning was performed to assess the void volume (as a percentage) at three root levels. After the root fillings were removed, second micro-CT scanning was conducted to evaluate the amount of remaining root filling material. The Kruskal-Wallis

H

test and post hoc analysis were used for between-group comparisons. The Mann–Whitney

U

test was used for comparisons between canals with and without an isthmus (

p
<
0.05

). In the EndoSeal MTA group, the void volume and remaining filling materials were higher irrespective of the presence or absence of an isthmus. In apical lesions in the EndoSeal MTA group, the void ratio was significantly lower, and there was a significantly higher amount of remaining filling material. Regardless of the presence of an isthmus, the amount of remaining filling material of the EndoSeal + PUI group was reduced to a similar degree as the AH plus group. When performing retreatment for root canals filled with EndoSeal MTA, removal of the filling material can be more difficult in the apical region. The additional use of PUI can improve the efficacy of removal.
Personalized Travel Recommendation Based on the Fusion of TGI and POI Algorithms
Authors: Fan Lu , Zhang Wenliang
Published: January 2022

On the way to travel, the public expect to get a tourism experience with low cost, convenient travel, and high comfort. At the same time, they also have different tourism needs such as history and culture, natural landscape, and food shopping. To address the problem that traditional travel route recommendation algorithms have limited accuracy and only analyze text or pictures alone, we propose a personalized travel route recommendation algorithm that integrates text and photo information from travelogues and obtain the historical tourism footprint of tourists by analyzing travel notes. According to the frequency and cooccurrence of scenic spots in the travel notes and the number of photos taken by each scenic spot, the popularity of scenic spots and the interest preferences of various types of tourists are analyzed. Under the given starting and ending points or passing points, the optimal tourism route generation method is designed. Experiments on the real data set of Ctrip Travel website show that the recommendation accuracy of this algorithm is significantly improved compared with the traditional algorithm which only uses travel notes text or photos. Compared with the algorithm that only considers the popularity of interest points or tourists’ interest preferences, the accuracy of the route recommended by the algorithm is improved. Compared with the algorithm that only considers the cooccurrence of scenic spots or only considers the influence of photos, this algorithm can obtain a better popularity score of scenic spots. This method integrates the two kinds of information including picture and text, fully considering the interest of users with high practicability.
The Construction of Folk Sports Featured Towns Based on Intelligent Building Technology Based on the Internet of Things
Authors: Li-yun Zhou , Cheng-ke Wang , Qiang Zhang
Published: January 2022

With the emergence of the Internet of Things, technology and Internet thinking have entered traditional communities, and combined with traditional technologies, many new and better management methods and solutions have been born. Among them, the concept of intelligent buildings is also known to people. Based on big data technology, cloud computing technology, and Internet of Things technology, smart buildings provide smart and convenient devices and services for smart device users. The Internet of Things technology is entering our lives at an unimaginable speed. It has been applied in many fields. Smart home, smart transportation, smart medical, smart agriculture, and smart grid are widely used in the Internet of Things technology. The application of Internet of Things technology to the construction of folk sports characteristic towns is of great significance. The construction of folk sports characteristic towns and the protection of intangible cultural heritage have the same purpose and interoperability of elements as the development of traditional cities. From the perspective of protecting folk culture and intangible cultural heritage, it is effective to promote the development of small towns with folk custom characteristics. Based on the research on the construction of folk-custom sports towns, this paper proposes a series of data model analysis and analyzes the proportion of sports preferences in the survey of volunteers in the folk-custom sports towns. The final result of the research shows that the ball games sports personnel accounted for the largest proportion, with 156 people accounting for 48.15%. This shows that about half of the people like ball sports, which proves that ball sports should be the mainstay of folk sports towns, and other sports should be supplemented by other sports.
Antioxidant and Anti-Inflammatory Activities of Phytochemicals from Ruellia tuberosa
Authors: Thi Pham Trinh Nhat , Nguyen Tuan Trong , Le Thi Nguyen Thuy , Nguyen Tran An Minh , Nguyen Tuan Ngoc , Tong Danh Thanh , Tien Le Dung
Published: January 2022

In Vietnam, the aerial parts of Ruellia tuberosa L. are used to treat stress oxidation and inflammatory symptoms in diabetes mellitus. The present study was designed to determine the antioxidant and inflammatory inhibition activities of Ruellia tuberosa L. extract (RTE) and those of the isolated compounds by column chromatography. The crude ethanol extract and ethyl acetate fraction exhibited potent antioxidant activity in the 2,2-diphenyl-1-picryl-hydrazyl-hydrate (DPPH) and 2,2-azinobis-(3-ethylbenzothiazoline-6-sulfonate) (ABTS) assays with an IC50 of 25.18 and 14.71 (DPPH test) and 18.22 and 15.27 µg/ml (ABTS test), respectively. The RTE contained high concentrations of polyphenols (308.21 mg GAE/g) and moderate concentrations of flavonoids (97.80 mg QE/g). In the anti-inflammatory screening assay, the crude ethanol extract, ethyl acetate, and methanol fractions suppressed the release of IL-6 and nitric oxide production, but the production of IL-10 was not enhanced in LPS-induced RAW 264.7 cells. Three potential anti-inflammatory compounds as hispidulin (6), physalin E (7), and physalin D (8) along with five other compounds named myricitrin (1), afzelin (2), apigenin (3), taraxerol (4), and lupeol (5) were isolated and identified from the ethyl acetate fraction. Physalin D (8) exhibited a strong, dose-dependent anti-inflammatory activity by inhibiting the production of IL-6 proinflammatory cytokines; however, the IL-10 expression was independent of its concentration in macrophages at noncytotoxic concentrations ranging from 5 to 40 μg/mL. Based on the data obtained, compounds 6–8 sourced from Ruellia tuberosa L are potentially bioactive compounds for the treatment of inflammation symptoms in type 2 diabetes mellitus.
Effect of Continuous Care Combined with Constraint-Induced Movement Therapy Based on a Continuing Care Health Platform on MBI and FMA Scores of Acute Stroke Patients
Authors: Yingying Pan , Zang Lixin , Wang Xiaojie , Yang Xiuqin
Published: January 2022

Background and Objective. The study was carried out under the background that out-of-hospital rehabilitation of acute stroke patients is of great importance for the recovery of nerve and limb functions. We aimed to investigate the effects of continuous nursing combined with CIMT by a health platform on the limb motor function and quality of life in acute stroke patients. Methods. 68 acute stroke patients admitted to our hospital from July 2018 to July 2019 were selected as the study participants and divided into group A and group B based on the odd and even numbers of their admission numbers, with 34 cases in each group. Patients in group B accepted the routine rehabilitation exercise, while patients in group A accepted the continuous care combined with constraint-induced movement therapy (CIMT) under a health platform, so as to compare their upper limb function recovery by the Fugl–Meyer assessment (FMA) and improved median Barthel index (MBI). Results. The general information of the two groups were not obviously different (

P

 > 0.05) but comparable; after intervention, the FMA scores (38.42 ± 7.62 vs 31.22 ± 7.25) and MBI scores (78.63 ± 6.52 vs 70.24 ± 6.48) of patients in group A were significantly higher than those of group B (

P

 < 0.001); the activities of daily living (ADL) and trunk control test (TCT) scores at T1, T2, and T3 of group A were significantly higher than those of group B (

P

 < 0.05); at 6 months after discharge, the self-concept, self-care skills, self-care, self-responsibility, health knowledge level, and total ability scores of patients in group A were significantly higher than those in group B (

P

 < 0.05); the Generic Quality of Life Inventory-74 (GQOL-74) scores after intervention of the two groups were significantly higher than those before intervention (

P

 < 0.05) and those of group A were significantly higher than those of group B (72.13 ± 4.69 vs 63.19 ± 4.72;

P

 < 0.05); when comparing with group B, group A presented significantly higher walking speed and gait period and lower support phase (

P

 < 0.05). Conclusion. The combination of continuous care and CIMT under a health platform can effectively promote the rehabilitation of upper limb functions and improve the activities of daily living and trunk control for acute stroke patients, with an effect better than conventional rehabilitation exercises, which is worthy of promotion.
Optimization of Data Acquisition Link of University Students’ Physical Health Testing System
Authors: Zhai Xiaohui , Li Yuanle , Zhong Chunli , Zhong Cheng , Luo Yunke
Published: January 2022

University students’ physical health test is an important part of university physical education. The data obtained by the physical health test play an extremely important role in the field of students’ physical health research. This paper clarifies the current situation of data collection of the physical health test for college students by sorting out the development status and trend of the physical health test system in China. To further ensure the accuracy and validity of the physical health test data, this article puts forward the corresponding optimization measures for the data collection link of the existing physical health testing system given the problems existing in the implementation of university students’ physical health tests. Optimization measures are as follows: (1) add a test data collection type for test video collection; (2) optimize the authentication process to increase face recognition; and (3) enhance posttest test data management by stamping time.
A Formal Representation of the Semantics of Structural Geological Models
Authors: Zhan Xianglin , Lu Cai , Hu Guangmin
Published: January 2022

A structural geological model describes the structure of subsurface and plays an important role in the exploration of mineral and petroleum resources. Despite the widespread use of three-dimensional geological models, the theoretical research of informatics in the field of structural geology is still very limited. We have noticed a lack of methods for integrating explicit semantics of field observation data and geophysical data into geological models. The existing model representation methods focus on accurately representing the geometric morphological information of underground structures, ignoring the high-level semantics implied in the model. The formal representation of the semantic information is necessary to promote the development of intelligent methods in geomodeling and geophysical inversion. In this paper, we propose a new framework to formally represent the semantics of structural geological models with a clear distinction of geometric and geological semantics. For the geometric semantics, based on the extension of the 9-intersection model, we mathematically define the spatial topological relations between geometric objects that make up the geological model. For the geological semantics, we define the geological contact and compositional relations between geological bodies and geological surfaces and reveal the temporal implications of these geological relationships. We design a multilayer heterogeneous network as a computer characterization of the semantics of the geological model. A better representation of semantic information aids in the creation and validation of geological models, as well as management, queries, and analyses of geological knowledge.
Dynamic Simulation and Conceptual Layout Study on a Quad-Plane in VTOL Mode in Wind Disturbance Environment
Authors: Li Fan , Song Wen-Ping , Song Bi-Feng , Jiao Jun
Published: January 2022

Quadrotor fixed-wing hybrid vertical take-off and landing (VTOL) UAV, the so-called Quad-Plane, is susceptible to wind disturbance during the VTOL mode, which reduces its stability and limits its application. In order to dynamically analyze its response characteristics to wind disturbance and effectively optimize the wind disturbance rejection performance in VTOL mode, a dynamic flight simulation system based on the 6-DoF equations is established, in which the aerodynamic model of the Quad-Plane is established based on the wind tunnel test, the axial and lateral forces and moments of the rotor in wind disturbance are obtained through CFD simulation, and the Brushless DC (BLDC) motor, wind disturbance, and flight controller are modeled based on actual characteristics. The simulation system is verified and validated by comparing the simulation results with test results of a 5 kg real Quad-Plane. Using this system, the response characteristics of the Quad-Plane to the discrete and continuous wind disturbance are studied. In addition, the influences of major conceptual layout parameters that affect the wind disturbance rejection performance, such as take-off weight, weight distribution, Center of Gravity (CG) position, rotor incline angle, arm length, and arm angle, are studied. Finally, the approaches on designing a Quad-Plane with better wind disturbance rejection performance during the conceptual layout design are presented.
Correlation between Immunohistochemical Markers in Hepatocellular Carcinoma Cells and In Vitro High-Throughput Drug Sensitivity Screening
Authors: Feng Guo-Ying , Cheng Yu , Chen Kai , Shi Zheng-Rong
Published: January 2022

Aim. This study analyzed the correlation between immunohistochemical markers in hepatocellular carcinoma cells and the results of in vitro high-throughput drug sensitivity screening, to provide a reference for individualized drug treatment in patients with liver cancer. Methods. Seventy-four patients with hepatocellular carcinoma were included in this study from December 2019 to June 2021, and their liver cancer cells were used for in vitro high-throughput drug sensitivity screening. According to the screening results, the patients were divided into relatively sensitive and insensitive groups, and the correlations between sensitivity and immunohistochemistry results were analyzed statistically. Results. Alpha-fetoprotein (AFP)-positive liver cancer cells were significantly more sensitive to gemcitabine than AFP-negative cells (χ2 = 6.102,

P
=
0.014

). AFP was also positively correlated with sensitivity of liver cancer cells to three combined regimens containing oxaliplatin (L-OHP) and epirubicin (EPI) : L-OHP + EPI + irinotecan + 5-fluorouracil (5-FU), L-OHP + irinotecan + EPI, and L-OHP + EPI (χ2 = 8.168,

P
=
0.004

, χ2 = 5.705,

P
=
0.017

, and χ2 = 8.275,

P
=
0.004

, respectively). Conclusion. Gemcitabine and L-OHP + EPI + irinotecan + 5-FU, L-OHP + EPI, and L-OHP + irinotecan + EPI were more effective against AFP-positive compared with AFP-negative liver cancer cells according to in vitro high-throughput drug sensitivity screening. These results may guide the selection of personalized drug treatments for patients with advanced liver cancer in the future but still need further clinical studies to confirm.
Citrus sinensis and Musa acuminata Peel Waste Extract Mediated Synthesis of TiO2/rGO Nanocomposites for Photocatalytic Degradation of Methylene Blue under Visible Light Irradiation
Authors: Olana Mulugeta Hirko , Sabir Fedlu Kedir , Bekele Eneyew Tilahun , Gonfa Bedasa Abdisa
Published: January 2022

Water pollution caused by various natural and artificial sources such as expansion of industrialization, rapid increment in population size, the threat of climate change, and development in urbanization takes a serious attention. Due to this fact, various protocols and techniques were adopted for the treatment of such polluted water. In the present findings, TiO2 nanoparticles (NPs) and TiO2/rGO nanocomposites (NCs) were synthesized using titanium tetra butoxide in the presence of Citrus sinensis (CS) and Musa acuminata (MA) peel waste extract as a capping, reducing, and stabilizing agent. The synthesized NPs and NCs were characterized using thermogravimetric‐differential thermal analysis (TGA/DTA), X‐ray diffraction (XRD), scanning electron microscope (SEM), high resolution transmission electron microscopy (HR‐TEM), selected area electron diffraction (SAED) pattern, ultraviolet diffuse reflectance spectroscopy (UV‐DRS), and Fourier transform infrared (FTIR) spectroscopy. The synthesized NPs and NCs were investigated as green alternative photocatalyst for the degradation of methylene blue (MB) dye under visible light irradiation. Thermal analysis results confirmed that the green synthesized TiO2 NPs were found to be too stable above 550°C. XRD analysis result showed that the average crystalline size of CS and MA mediated synthesized TiO2 NPs with various volume ratios was in the range of 7.3–27.3 nm and 13.4–22.4 nm, respectively. The average crystalline size of CS and MA peel extract template synthesized TiO2/rGO NCs was found to be in the range of 7.5–15.3 and 11.2–12.5 nm, respectively. The band gap energy was calculated to be in the range of 3.17–3.29 eV and 3.10–3.38 eV for the CS and MA mediated synthesized TiO2 NPs, respectively. Eg of CS and MA peel extract template formed TiO2/rGO NCs was found to be in the range of 2.85–3.11 eV and 3.07–3.11 eV, respectively. SEM analysis proved that the various synthesized TiO2 NPs and TiO2/rGO NCs were spherical in shape and the absence of any other foreign materials confirmed the purity of the corresponding nanocatalysts. In addition, TEM, HRTEM, and SAED analysis confirmed that the structures of the synthesized nanocatalysts were spherical in shape and the catalysts were too crystalline and the result was found to fit with the XRD result. Among the synthesized various volume ratios of TiO2 nanocatalysts, high percentage of degradation (62% and 58.2%) was achieved using TiO2‐2c and TiO2‐2 m, respectively. Moreover, 94.28% and 94.25% of MB degradation were achieved in the presence of TiO2/rGO‐1.5c and TiO2/rGO‐1.5c nanocomposite photocatalysts, respectively.
Immunomodulatory Effect of Lycium barbarum Polysaccharides against Liver Fibrosis Based on the Intelligent Medical Internet of Things
Authors: Han Yanzhen , Zhou Yan , Shan Tieying , Li Wei , Liu Haiping
Published: January 2022

Lycium barbarum polysaccharide (LBP) is the main active component of Lycium barbarum and has many beneficial effects, including neuroprotection, antiaging, and antioxidation. This study mainly explores the immunomodulatory effect of Lycium barbarum polysaccharides against liver fibrosis based on the intelligent medical Internet of Things. This measure emphasizes that the current effective methods and methods for the treatment of liver cancer are mainly combined treatments of Western medicine and Chinese medicine. These treatments have a certain effect in preventing liver cancer, reducing recurrence, and reducing side effects. Among them, chemotherapy has unique advantages in improving the quality of life and prolonging survival. With the development of medical science and technology, the clinical efficacy and efficacy of traditional Chinese medicine in the treatment of liver cancer are constantly improving. The mechanism is also studied from many aspects. The treatment time of LBPs on fibrotic hepatocytes was set to 24 h. Take liver fiber cells in logarithmic growth phase and incubate them at 37°C for 24 h. The whole process uses a temperature sensor for intelligent temperature control. In the experiment, groups of LBPs with different concentrations and different molecular weight ranges were set up and each group had 6 multiple holes. The original medium was aspirated and replaced with a medium containing different concentrations of LBPs (12.5, 25, 50, 100, and 200 μg/mL) and cultured for 24 h. Based on the previous research, this study used in vitro cell experiments, microscopic observation, and MTT method to verify whether Lycium barbarum polysaccharides inhibit the proliferation of human liver cancer cells in vitro and whether they cooperate with the chemotherapy drug fluorouracil to play a tumor-killing effect. Animal experiments, using ELISA, HE staining, and other methods, explore the molecular and immunological mechanisms of LBP’s antiliver cancer effect from the perspective of Th/Th2 differentiation balance and DC function, in order to provide experimental evidence for Chinese medicine polysaccharides in cancer immunotherapy and application. At different LBP concentrations (0 μmol/L, 5 μmol/L, 10 μmol/L, and 15 μmol/L), the inhibition rates were 0.80%, 20.06%, 35.44%, and 55.39%, respectively. This study provides a new method for large-scale expansion of hepatocytes in vitro, laying a stronger foundation for biological treatment of liver fibrosis.
G-Protein-Coupled Receptor Kinase-Interacting Protein 1 (GIT1) Promotes Head and Neck Squamous Cell Carcinoma Metastases via Activating the PI3K/AKT/mTOR Signal Pathway
Authors: Xu Runze , Xu Ran , Wang Yuanxiang , Wang Weixing , Jiang Lingling , Gong Shishun
Published: January 2022

Objective. GIT1 is identified as a novel tumor oncogene in breast cancer. In this article, we aimed to explore the role of GIT1 in the progression of head and neck squamous cell carcinoma (HNSCC). Methods. GIT1 expression in HNSCC was detected by RT-qPCR, immunohistochemistry assay, and Western blot. HNSCC cell proliferation, migration, and invasion were examined by CCK-8 assay, Wound healing assay, and Transwell assay, respectively. Cell apoptosis was detected by flow cytometric analysis. Results. In our study, GIT1 was notably upregulated in HNSCC tissues and cells. Moreover, GIT1 expression level had positive corelation with pathological grade and nodal status of HNSCC. Functional experiments showed that knockdown of GIT1 restrained HNSCC proliferation, invasion, migration, and EMT and facilitated cell apoptosis. Furthermore, GIT1 knockdown was found to restrain HNSCC tumor growth and lung metastasis. Additionally, PI3K/AKT/mTOR signal pathway inhibitors suppressed the effect of GIT1 on HNSCC cell progression. Conclusion. GIT1 was upregulated in HNSCC and facilitated HNSCC cell progression by inducing PI3K/AKT/mTOR signal pathway. Therefore, we suggested that GIT1 might be a potential target for HNSCC treatment.
Automatic Scoring of Spoken Language Based on Basic Deep Learning
Authors: Cheng Zhong , Wang Zonghua
Published: January 2022

The oral English test in domestic universities requires teachers to modify a large number of candidates’ oral recordings. This is the work of using time repeatedly. Using the CALL system to realize the automation of conversation recording can reduce the burden of teachers’ work. Therefore, it is of great practical significance to develop an automatic and accurate scoring system for oral English. With the development of artificial intelligence, deep learning technology has been gradually applied in various fields. Similarly, in the application of oral scoring, deep learning technology makes the implementation of such a system possible. Based on the deep learning technology, this paper proposes an automatic scoring algorithm for spoken language and implements a detailed design and evaluation system. The system consists of two modules. The pronunciation standard of spoken pronunciation and the content of spoken pronunciation are scored, and the sum of these two scores is the final score. Finally, this paper uses 650 oral English recordings from a college English test to train the artificial neural network. Experimental results show that if the training data set is small, the BP network model can obtain better comprehensive evaluation performance.
Experimental Analysis of the Thermal Performance of a Latent Heat Energy of Helical Coil for the Application of Solar Energy
Authors: Jayakumar T. , Rubavathy S. Jaanaa , Karpagam R. , Diwakaran S. , Jayadhas S. Arockia , Ahamed Maqusood , Sureshkumar Shanmugam
Published: January 2022

The latent thermal power storage system has more characteristics than the sensitive storage system. The heating system is a process of releasing and absorbing heat energy using phase transfer material (PCM) and it provides more efficient energy than sensible heat storage. This also consist of high energy storage and high density. It provides high heat transfer in low volume and thereby enhances heat transfer. This enhances the capacity and efficiency of the EFU while extending the service life. The coil tube is designed for latent thermal energy storage to implement and enhance thermal performance during the loading and unloading process. The offloading time, however, was not affected by the flows. Higher throughput has also been shown to improve the effectiveness of recovery. The direction of flow of the HTF did not affect the total time of loading and recharging but affected the temperature changes of the PCM in the energy storage element. It is intended to predict the ability to store maximum energy as higher energy efficiency during the phase shift process. Parameters such as the mean temperature of the PCM, the growth of the melting front, the energy efficiency, and the number of generations of entropy are studied.