bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tribological properties of 100% cellulose nanofiber (CNF) molding under dry- and boundary lubrication-conditions at CNF/steel contacts
Authors: Okubo Hikaru , Nakae Ryota , Iba Daisuke , Yamada Kazushi , Hashiba Harumi , Nakano Ken , Sato Kaisei , Sasaki Shinya 
Published: October 2022

Abstract
Recently, the cellulose nanofiber (CNF), which is a pure, plant-derived material, has attracted considerable attention owing to its excellent mechanical properties such as low weight (one-fifth that of steel) and high Young’s modulus (five times that of steel) as a fiber. Novel methods for producing 100% CNF bulk structural materials have been developed. However, the tribological properties of CNFs have never been investigated although their mechanical properties are well-known, which are comparable to those of some of the conventional structural materials. Herein, the tribological properties of a novel biomass material, 100% CNF molding, were investigated under dry- and boundary-lubrication conditions at various temperatures for CNF/steel contacts. The friction test results showed that the friction coefficient and wear volume of the CNF molding increased with the test temperature for the CNF/steel tribopair under the dry-sliding conditions. Conversely, upon the lubrication with pure-poly-alfa-olefin, no significant temperature dependence of the friction and wear properties was observed. The surface analytical results revealed that the amorphization of the CNF molding progressed on the worn surface, especially under the dry-sliding conditions at a relatively high temperature. All the results suggested that the friction and wear performance of the 100% CNF moldings strongly depend on the sliding test conditions, and the amorphization process of the CNF molding can affect its friction and wear performance.
Pilot molecular assessment for components and capability of Northern Nile crab Potamonautes niloticus soft tissue extract for reduction of early obesity markers
Authors: Galal-Khallaf Asmaa , Shetaia Aya , Khalifa Shaden A. M. , Zou Xiaobo , Sakr Hanem H. , Chen Lei , Shehata Awad , Guo Zhiming , El-Seedi Hesham R. , Mohammed-Geba Khaled 
Published: October 2022

Abstract
Obesity is a serious global problem that is considered a great pandemic. It was related to many non-communicable diseases, including type 2 diabetes mellitus (T2DM). Crab (Crustacea: Decapoda) is one of the healthiest sea foods all over the world, being very rich in unsaturated fatty acids, especially in the female gonads and hepatopancreas. Therefore, this study was designed to explore the anti-obesity effect for the soft tissue extract of the female Nile crab Potamonautes niloticus. The chemical constituents of methanol extract from crab´s meat and soft Dichloromethane were evaluated using Liquid Chromatography with tandem mass spectrometryand Nuclear Magnetic Resonance. Also, the effect of this extract on obesity induced in zebra fish adults was studied in vivo, using real time PCR (qPCR) quantification of different lipid-metabolizing enzymes´ genes. More specifically, these analyzed transcripts were for enzymes related to de novo lipogenesis [i.e., fatty acids synthase (FASN) and acetyl- CoA carboxylase alpha (accα)]; adipogenesis [i.e. diacylglycerol O-acyltransferase 2 (dgat2)]; and lipid catabolism through β-oxidation [i.e. acetyl-CoA oxidase 1 (acox1)]. Moreover, the body contents of free cholesterol (TC) and triglycerides (TG) were assessed. The results showed that the extract contains amino acids such as cyclo-(Ala-4-hydroxy-Pro, Ile-pro, isoleucyl-proline, cyclo-(Leu-Leu), cycloleucylleucine, valyl-Leucine, L-valyl-L-phenylalanine, cyclo(L-leucyl-L-phenylalanyl), cyclo-[Tyr-(4-hydroxy-Pro)], and leucyl-phenylalanine); long chain unsaturated fatty acids such as (9-octadecenoic acid, 13-keto-9Z,11E-octadecadienoic acid, (+/-)-11-Hydroxy-5Z,8Z,12E,14Z,17Z-Eicosapentaenoic acid, and (.+/-.)-17-hydroxy-4Z,7Z,10Z,13Z,15E,19Z-docosahexaenoic acid); long chain saturated fatty acids such as (3-Hydroxyoctadecanoic Acid and 1-stearoyl-2-hydroxy-sn-glycero-3-phosphocholine); sphingolipids; fatty amide; and Monoacylglycerol. Furthermore, injection of crab extract to adult zebrafish induced a significant decrease of TG levels and the expression of the gene of the primary enzymes’ genes related to fatty acids β-oxidation, i.e., acox1. Meanwhile, crab extract injection induced significant down-regulation in the key lipogenic enzymes´ genes, i.e. accα, fasn, and dgat2. Therefore, P. niloticus soft tissue extract showed promising ingredients and capabilities that could reduce obesity through interference with lipids´ synthesis and stimulation of lipids´ degradation. Further investigations are recommended to elucidate the mechanism of action of Nile crab bioactive ingredients on obesity and other related health problems, such as T2DM.
Antiviral Therapy Inhibited HBV-reactivation and Improved Long-term Outcomes in Patients Who Underwent Radiofrequency Ablation for HBV-related Hepatocellular Carcinoma
Authors: Liu Jian , Shen Hao , Huang Shengyu , Lin Jianbo , Yan Zhenlin , Qian Guojun , Lu Zhenghua , Wan Xuying , Zhang Fabiao , Wang Kui , Zhang Yongjie , Li Jun 
Published: October 2022

Abstract
Background: The study aimed to examine the impact of antiviral therapy (AVT) on hepatitis B virus (HBV) reactivation and long-term outcomes after percutaneous radiofrequency ablation (PRFA) for HBV-related hepatocellular carcinoma (HCC).
Methods: Data on 538 consecutive patients who underwent PRFA for early-stage HBV-related HCC between 2009 and 2013 were reviewed. Propensity score matching (PSM) analysis was used to adjust for differences in baseline features between AVT and non-AVT groups. Tumor recurrence and overall survival (OS) rates were analyzed using the Kaplan-Meier method. Tumor recurrence patterns were also investigated. Logistic regression was used to identify the risk factors of viral reactivation.
Results: After PSM, 215 pairs of patients were generated. The AVT group had a lower 1-, 3-, and 5-year tumor recurrence rates (24%, 55%, and 67% vs 33%, 75%, and 85%, respectively) and a higher 1-, 3-, and 5-year OS rates (100%, 67%, and 59% vs 100%, 52%, and 42%, respectively) than non-AVT group (P<0.001 for both). Additionally, the intrahepatic distant recurrence and the later recurrence beyond 2 years after PRFA were significantly reduced in the AVT group compared with the non-AVT group (111/215 vs. 78/215, P=0.001; 39/109 vs. 61/91, P=0.012, respectively). HBV reactivation developed in 10.8% of patients after PRFA. AVT was identified as one of the independent risk factors of viral reactivation (odd ratio: 0.061, 95% confidence interval: 0.018-0.200).
Conclusions: AVT reduced recurrence rate and improved OS of HBV-related HCC patients undergoing PRFA, possibly by inhibiting viral reactivation and then decreasing intrahepatic distant recurrence and late recurrence.
Comprehensive chemical profiling of two Dendrobium species and identification of anti-hepatoma active constituents from Dendrobium chrysotoxum by Network Pharmacology
Authors: Xia Jie , Jiani Yu , Jiahao Fang , Ganggui Lou , Feng Yin , Zhongyu Xu , Yuan Yuan , Tinggang Zhang , Zongsuo Liang , Zhang Xiaodan 
Published: October 2022

AbstractBackgroundD. nobileandD. chrysotoxumwere important species of the genusDendrobiumand has great economic and medicinal value. The material basis of the medicinal effect ofD. nobileandD. chrysotoxumis still unclear, and the biomarkers associated with the anti-cancer are not entirely clear so far. There is no scientific, universal and measurable quality control system, which greatly restricts the development of theDendrobiumindustry. This study focused on the comprehensive chemical profiling of twoDendrobiumspecies and identification of anti-hepatoma active constituents fromDendrobiumchrysotoxum by Network Pharmacology. Results Chemical profiling showed that altogether 65 phytochemicals were identified fromD. nobileandD. chrysotoxum, with major classes as alkaloids, terpenoids, flavonoids, bibenzyls and phenanthrenes. About 18 compounds were identified as the important differential metabolites inD. nobileandD. chrysotoxum. Furtherly, CCK-8 results showed that the extracts of stems and leaves ofD. nobileandD. chrysotoxumcould inhibit the growth of Huh-7 cells, and the anti-hepatoma activity of extracts were dose-dependent. Among the extracts, the extract ofD. chrysotoxumshowed significant anti-hepatoma activity. To find the material basis and mechanisms underlying the anti-hepatoma activity ofD. chrysotoxum.By constructing and analyzing the compound-target-pathway network, five key compounds and nine key targets were obtained. The five key compounds were chrysotobibenzyl, chrysotoxin, moscatilin, gigantol and chrysotoxene. The nine key targets GAPDH, EGFR, ESR1, HRAS, SRC, CCND1, HIF1A, ERBB2 and MTOR could be considered as the core-targets of the hepatoma activity ofD. chrysotoxumto hepatoma. Conclusions In this study, mass spectrometry-based molecular networking and multivariate statistical analysis was conducted to screen 18 differential metabolites inD. nobileandD. chrysotoxum. CCK-8 results showed thatD. nobileandD. chrysotoxumextracts could inhibit the growth of Huh-7 cells. The molecular network revealed chrysotobibenzyl, chrysotoxin, moscatilin, gigantol and chrysotoxene were identified as core components ofD. chrysotoxumon anti-hepatoma. This study compared the chemical composition differences and anti-hepatoma activities between the whole herbs ofD. nobileandD. chrysotoxum, and revealed the anti-hepatoma effects ofD. chrysotoxumand its potential underlying therapeutic mechanisms in a multi-target and multi-pathway manner.
Prevalence of chronic periodontitis in patients undergoing peritoneal dialysis and its correlation with peritoneal dialysis-related complications
Authors: Chen Zhihao , Deng Hai , Sun Kristine , Huang Zehui , Wei Shan , Lin Yunyao , Song Zhongchen , Liu Yingli 
Published: October 2022

Abstract
Objective:The microinflammatory state can influence the occurrence of dialysis-related complications in dialysis patients. Chronic periodontitis(CP), in which plaque biofilm is considered to be the initiating factor, is a chronic infectious disease in the oral cavity. It is still uncertain whether CP affects the microinflammatory state in peritoneal dialysis(PD) and the occurrence of dialysis-related complications.The purpose of this study was to investigate the correlation between the periodontal index and clinical parameters in peritoneal dialysis patients with CP and dialysis-related complications, including peritoneal dialysis-associated peritonitis (PDAP) and cardiovascular and cerebrovascular events(CCEs). Methods:This was a retrospective cohort study, and 76 patients undergoing PD were enrolled. Clinical parameters,the occurrence of PD-related complications and periodontitis-related indicators, including the gingival index(GI), plaque index(PLI), probing depth(PDD) and clinical attachment loss(CAL),were collected.Correlation analysis was used to explore the correlation between periodontal or clinical parameters and the occurrence of PD-related complications.
Results:All the patients had different degrees of periodontitis (mild 9.2%, moderate 72.4%, severe 18.4%); PPD was inversely related to serum albumin (r=-0.235, p=0.041);CAL has a negative correlation with serum C-reactive protein(rs=-0.242, p=0.035); PLI was positively correlated with serum calcium(r=0.314, p=0.006). Binary logistic regression analysis suggested that CAL was a risk factor for the occurrence of PDAP. There was no correlation between periodontal parameters and CCEs or poor prognosis.
Conclusion:CP is universally present in PD patients, and the presentation of periodontitis influences the systemic inflammatory state, nutritional status and calcium and phosphorus metabolism in PD patients. CP is a risk factor for PDAP.
Deep Reinforcement Learning-Based Edge Computing Offloading Algorithm for Software-Defined IoT
Authors: Zhu Xiaojuan , Zhang Tianhao , Zhang Jinwei , Zhao Bao , Zhang Shunxiang , Wu Cai 
Published: October 2022

Abstract

With the amount of data generated by Internet of Things (IoT) devices increase dramatically, the insufficient computing ability of terminal devices becomes obvious when processing massive computing tasks. The computing tasks need to be offloaded from resource-constrained devices to edge servers with stronger computing capability. It is a challenge for computing offloading to achieve global optimization with multiple objectives such as minimizing task completion times, optimizing energy consumption and maintaining load balancing as the network state and task demands dynamically change. This paper presents optimized edge computing offloading algorithm for software-defined IoT. First, to provide global state for making decisions, a software defined edge computing (SDEC) architecture is proposed. The edge layer is integrated into the control layer of software-defined IoT, and multiple controllers share the global network state information via east-west message exchange. Moreover, an edge computing offloading algorithm in software-defined IoT (ECO-SDIoT) based on deep reinforcement learning is proposed. It enables the controllers to offload the computing task to the most appropriate edge server according to the global states, task requirements, and reward. Finally, the performance metrics for edge computing offloading were evaluated in terms of unit task processing latency, load balancing of edge servers, task processing energy consumption, and task completion rate, respectively. Simulation results show that ECO-SDIoT can effectively reduce task completion time and energy consumption compared with other strategies.
Molecular recognition of SARS-CoV-2 spike protein with three essential partners: exploring possible immune escape mechanisms of viarl mutants
Authors: cheng yan , Zheng Dan , Zhang Derong , Guo Du , Wang Yueteng , Liu Wei , Liang Li , Hu Jianping , Shi Hubing , Luo Ting 
Published: October 2022

Abstract
The COVID-19 epidemic is raging around the world, including the emergence of viral mutant strains such as Delta and Omicron, posing severe challenges to people's health and quality of life. Full understanding life cycle of the virus in host cells helps to reveal inactivation mechanism of antibody and provide inspiration for the development of a new-generation vaccines. In this work, molecular recognitions and conformational changes of SARS-CoV-2 spike protein (SP) mutants (i.e., Delta, Mu and Omicron) and three essential partners (i.e., membrane receptor hACE2, protease TMPRSS2 and antibody C121) both were compared and analyzed using molecular simulations. Water basin and binding free energy calculations both show that the three mutants possess higher affinity for hACE2 than WT, exhibiting stronger virus transmission. The descending order of cleavage ability by TMPRSS2 is Mu, Delta, Omicron and WT, which is related to the new S1/S2 cutting site induced by transposition effect. The inefficient utilization of TMPRSS2 by Omicron is consistent with its primary entry into cells via the endosomal pathway. In addition, RBD-directed antibody C121 showed obvious resistance to Omicron, which may have originated from high fluctuation of approaching angles, high flexibility of I472-F490 loop and reduced binding ability. According to the overall characteristics of the three mutants, high infectivity, high immune escape and low virulence may be the future evolutionary selection of SARS-CoV-2. In a word, this work not only proposes the possible resistance mechanism of SARS-CoV-2 mutants, but also provides theoretical guidance for the subsequent drug design against COVID-19 based on SP structure.
Performance Analysis of Doubly Fed Induction Generator in Wind Energy Conversion System by Controlling Active and Reactive Power
Authors: Belayneh Beza Abebe , Tuka Milkias Berhanu 
Published: October 2022

Abstract
Wind energy has emerged as one of the sustainable power sources having extraction of maximum power as its major challenge. Thus the main purpose of this paper is to get the best control mechanisms for maximum power extraction in Doubly Fed Induction Generator (DFIG) based wind turbine. The proposed techniques used allow the generator to track the optimal operation points under a variable condition upon the model of DFIG, Wind Turbine, Machine and Grid Side Convertors, and controllers. This is carried on the MATLAB-Simulink platform with the main control algorithms of a Proportional-Integral (PI) Controller, Fuzzy Logic Controller (FLC), Sliding Mode Controller (SMC), and Super Twisted Sliding Mode Controller (STSMC). The most extensively used conventional PI controller in the real wind sector having a high overshoot with a prolonged settling time requires modification for every change in reference pattern. Hence, to ensure robustness against external disturbances, FLC and SMC are applied. However, it is found that the conventional SMC has a chattering problem. To improve it, the STSMC technique is implemented showing an improved performance of settling time, overshoot, and rise time for active power control. It is seen that PI has a settling time of 1.0351 sec while an overshoot is 3.9 %. Whereas, FLC has a settling time of 0.8021 sec with an overshoot of 2.8 %. Finally, STSMC has a settling time of 0.3314 sec and an overshoot of 2.2 %. This leads to the conclusion that the STSMC controller has better dynamic performance than others do.
Examining Reactivity to Intensive Longitudinal Ecological Momentary Assessment: 12-month Prospective Study
Authors: Cajita Maan Isabella , Rathbun Stephen L. , Shiffman Saul , Kline Christopher E. , Imes Christopher C. , Zheng Yaguang , Ewing Linda J. , Burke Lora E. 
Published: October 2022

Abstract
Purpose

To examine the association between intensive, longitudinal ecological momentary assessment (EMA) and self-reported eating behaviors.

Methods

Secondary analysis of the EMPOWER study—a 12-month observational study that examined the microprocesses of relapse following intentional weight loss using smartphone-administered EMA—was conducted. Participants were asked to complete four types of EMA surveys using a mobile app. For this analysis, only the number of completed random EMA surveys was used. Using linear mixed-effects modeling, we analyzed whether the number of completed random EMA surveys was associated with changes in self-reported dietary restraint, dietary disinhibition, and susceptibility to hunger measured using the Three-Factor Eating Questionnaire (TFEQ).

Results

During the 12-month study, participants completed a mean of 1,062 random EMA surveys (range: 673-1,362). The number of completed random EMA surveys was not significantly associated with TFEQ scores. However, there was a marginally significant main effect of the number of EMA surveys on disinhibition (p = 0.08) and an interaction between study interval and the number of EMA surveys on restraint (p = 0.08).

Conclusions

Intensive longitudinal EMA did not influence self-reported eating behaviors. The findings suggest that EMA can be used to frequently assess real-world eating behaviors with minimal concern about assessment reactivity. Nonetheless, care must be taken when designing EMA surveys—particularly when using self-reported outcome measures.
Level of evidence: Level III, prospective observational study
Rasch analysis of the Chinese version of the Clinically Useful Depression Outcome Scale in patients with major depressive disorder
Authors: Zhong Jing , Ma Hai-Yan , Wang Xue-Mei , Huang Xiao-Jie , Xu Ming-Zhi 
Published: October 2022

Abstract
Objective
To examine the psychometric properties of the Chinese version of the Clinically Useful Depression Outcome Scale (CUDOS) in the Chinese patients with major depressive disorder (MDD) using Rasch analysis.
Method
The sample consisted of 283 patients with MDD (69% females). The Rasch model was applied to examine the overall fit of the Chinese version of CUDOS and the fit of the 18 items to the Rasch model. Dimensionality, item-model fit, differential item functioning (DIF), reliability, ordering of response categories and targeting were tested to examine the psychometric properties of the Chinese version of CUDOS.
Results
Rasch analysis demonstrated the unidimensionality of the Chinese version of CUDOS. Of the 18 items, three items (item 4, item 5, item 6) showed misfit in the model. After merging item 4 into item 3 and item 6 into item 5, the overall model fit improved. The person separation index (PSI) was 3.0 and the person reliability coefficient was 0.90. No evidence of significant differential item functioning(DIF) was found when associated with gender and age. No disordered category and threshold of the rating response were observed, which meant the response categories setting was reasonable. The mean ability of person was − 0.53.
Conclusion
The results suggested that the Chinese version of CUDOS has acceptable psychometric properties. In order to improve the quality and applicability of the Chinese version of CUDOS, the merging of item 4 into item 3 and item 6 into item 5 are suggested.
Artificial intelligence for prediction of chronic thromboembolic pulmonary hypertension using electrocardiography
Authors: Kocabay Gonenc , Kivrak Tarik , Tuncer Turker , Dogan Sengul , kobat mehmet ali 
Published: October 2022

Abstract
Background: Screening and accurate diagnosis of chronic thromboembolic pulmonary hypertension(CTEPH) are critical for managing the progression and preventing associated mortality; however, there are no tools for this purpose. We developed and validated an artificial intelligence (AI) algorithm for predicting CTEPH using electrocardiography (ECG).
Methods: ECG signals were obtained from 54 regular and 23 CTEPH patients to test the technique. A dataset was created by converting the ECG results to digital. The 12-channel ECG signal received from 77 individuals is 924x1300 in size. The end-point was the diagnosis of CTEPH. By applying the suggested Nigerian motif pattern method to this data set, we obtained a feature matrix of 924x15010. FSCmRMR algorithm determined the most influential 947 characteristics among 15010 features and obtained a matrix of 924x947. We used a decision tree, SVM(Support Vector Machine), and KNN(K-Nearest Neighbour )algorithms to classify the selected most weighted features.
Results: We achieved 98.05% success with the decision tree algorithm, 99.89% with the SVM algorithm, and 99.67% with the KNN algorithm. AI algorithm focused on each patient's S-wave, P-wave, and T-wave by QRS complex characteristics.
Conclusion: The AI algorithm demonstrated high accuracy for CTEPH prediction using 12-lead and single-lead ECGs.