bluuebunny/crossref_metadata_2025_split huggingface dataset:
Phytochemistry and Antiviral Properties of Two Lotus Species ‎Growing in Egypt
Authors: Youssef Ahmed Mohamed Mohamed , EL-Swaify Zeinb Ahmad Said EL-Swaify , Maaty Doaa  Ahmed ‎Mohamed , Youssef Mohamed Mohamed 
Published: March 2022

Background: Lotus arabicus L and Lotus glaber Mill. belong to the family Fabaceae, and they grow in the wild in ‎Egypt and have different therapeutic uses in folk medicine. Objectives: This study aimed to evaluate the phytochemical profile and ‎antimicrobial properties of the methanolic extracts of two Lotus spp. growing in Egypt, L. ‎arabicus and L. glaber. Material and methods: Gas chromatography-mass spectrometry was used to identify the compounds of the extracts of two Lotus species. An MTT colorimetric assay and the disc diffusion method were performed to investigate the antiviral and antimicrobial activities of two lotus species, respectively. Results: The n-hexane and methanol extracts of L. ‎arabicuscontained high percentages of alkane hydrocarbons, such as 5-methyloctadecane, ‎while L. glaber contained dodecane. The major compounds in the methanol extract of L. ‎arabicus were hexadecanoic acid methyl ester and dodecanoic acid,2,3-bis(acetyloxy)propyl ‎ester. The major compounds in the methanol extract of L. glaber were palmitic acid and ‎lucenin 2. The indole alkaloid ditaine was found only in L. arabicus. This alkaloid was ‎identified for the first time in the genus Lotus. The antimicrobial properties of the extracts of ‎the two Lotus species showed that the n-hexane extract of ‎both Lotus species may have potential antifungal activity against Candida parapsilosis and ‎Aspergillus flavus. Moreover, the methanolic extracts of both Lotus species have potential ‎antiviral activity against the coxsackie B virus, but only the L. arabicus extract showed ‎activity against the hepatitis A virus.‎ Conclusion: Lotus arabicus might have potential antifungal or antiviral activity greater than L. glaber.
On solving uncooperative linear bilevel multi-follower programming problems
Authors: Moslemi Fatemeh , Sadeghi Habibeh 
Published: March 2022

The relationship between the reference-uncooperative linear bilevel two-follower decision making and the multi-objective decision making has been recently considered (Sadeghi and Moslemi, 2019). In this paper, we address the foregoing relation for the
uncooperative linear bilevel multi-follower programming (ULBMFP) model with followers. Furthermore, we consider some geometric properties of the feasible solutions set of the ULBMFP problem. Moreover an algorithm to find an optimal solution for the ULBMFP problem was proposed. Ultimately, some numerical examples to illustrate the proposed algorithm were provided.
In silico Prediction of Molecular Docking between Chicken BRD2 and Newcastle Disease Virus Matrix Protein to Elucidate Host-pathogen Interaction
Authors: Singh Paramvir , Mukhopadhyay C.S. , Dash Shakti Kant 
Published: March 2022

Background: Newcastle disease is one of the most contagious viral diseases caused by the Newcastle disease virus (NDV) which causes a huge loss in the terms of economy as well as mortality level in the poultry sector. The viral matrix protein is one of the proteins which helps in the attachment of virus, budding and assembly of progeny virions in the host cell. Host-pathogen interaction plays a very important role in the changeover of genetic diversity in organisms. Methods: The amino acid sequences of chicken BRD2 gene and matrix protein of NDV were used for structure prediction and visualization of protein-protein interaction between BRD2 and matrix protein by using Discovery Studio software. The nucleotide sequences of both genes were used for evolutionary analysis using MEGA7 software followed by selection pressure analysis using online Datamonkey server. Result: The results indicated that the ligand was attached with the matrix protein, which acts as a receptor on the virus surface. The purifying selection has been evident for the viral matrix protein gene. The docking of viral protein with host BRD2 protein has been detected in the study which further warrants experimental validation. In conclusion, the viral matrix protein interacts at amino acid position Tyrosine-148, Valine-339, Alanine-341 with ligand present on the chicken BRD2 protein. The evolutionary analysis revealed that the matrix protein of NDV R2B strain was the closest to that of Peacock, pigeon, duck and quail however, it exhibited maximum distance with the chicken NDV from Ireland, Vietnam and Haryana state of India.
Outcomes and Survivorship at a Median of 8.9 Years Following Hip Arthroscopy in Adolescents with Femoroacetabular Impingement
Authors: Fukase Naomasa , Murata Yoichi , Pierpoint Lauren A. , Soares Rui W. , Arner Justin W. , Ruzbarsky Joseph J. , Quinn Patrick M. , Philippon Marc J. 
Published: March 2022

Background:
Because of the unique theoretical surgical risks, including osteonecrosis, acute iatrogenic slipped capital femoral epiphysis, and epiphyseal injury, the optimal treatment strategy for femoroacetabular impingement (FAI) in growing adolescents has yet to be established. The aim of this study was to compare the clinical outcomes of primary arthroscopic treatment of FAI in growing adolescents with a matched adult group.

Methods:
Patients with FAI who underwent arthroscopic treatment with a minimum follow-up of 2 years were included. Patients with previous ipsilateral hip surgery, an Outerbridge grade of ≥3, a preoperative Tönnis grade of ≥2, or evidence of dysplasia (lateral center-edge angle of <25°) were excluded. Eligible patients who were ≤19 years old and whose proximal femoral physis had not yet closed were matched to adult (20 to 40-year-old) counterparts in a 1:1 ratio by sex, body mass index, and time of surgery. For the adolescents, cam resection was performed with a physeal-sparing approach. Outcome scores, including the modified Harris hip score (mHHS), Hip Outcome Score-Activities of Daily Living (HOS-ADL), and HOS-Sports-Specific Subscale (HOS-SSS), were prospectively collected.

Results:
Of the 196 eligible adolescents, 157 (80%) were pair-matched to adult controls, with a median postoperative follow-up of 8.9 and 6.6 years, respectively. Fourteen (9%) of the adolescents required revision hip arthroscopy compared with 18 adults (11%) (p = 0.46). No patient in the adolescent group had conversion to a total hip arthroplasty (THA), while 3 in the adult group had a THA (p = 0.25). For adolescents without subsequent hip surgery, the median mHHS improved from 59 preoperatively to 96 postoperatively; the HOS-ADL, from 71 to 98; and the HOS-SSS, from 44 to 94 (p < 0.001), which were significantly higher postoperative scores than those of the matched adults (p < 0.05) despite similar or inferior baseline scores. No complications were found during the office visit or at the final follow-up.

Conclusions:
Hip arthroscopy performed with a physeal-sparing approach for FAI in growing adolescents is safe and effective and yields superior clinical outcomes compared with those in a matched adult group.

Level of Evidence:
Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.
A Comparison between Klinkenberg and Maxwell-Stefan Formulations to Model Tight Condensate Formations
Authors: Sena Santiago Carla Jordana , Kantzas Apostolos 
Published: March 2022

Summary
Cyclic solvent (gas) injection is an efficient recovery method for condensate reservoirs. However, in tight, unconventional formations, the added complexity of low permeability results in more physics at play, beyond the widely used Darcy model for conventional reservoirs. In this work, a rigorous mass transfer model is implemented considering the real gas version of the Maxwell-Stefan formulation to evaluate cyclic injection schemes in tight condensate reservoirs. This model is then compared to the more widespread used Klinkenberg formulation, which does not include molecular diffusion. An evaluation is performed to check if a simplified formulation can be used to provide reasonable results in modeling production and enhanced recovery in tight condensate formations. Verification of the implemented equations is performed using experiments (Maxwell-Stefan model) and a commercial reservoir simulator (Klinkenberg model). Furthermore, the cell length used for the numerical studies is selected based on a sensitivity study to evaluate how numerical dispersion impacts recovery factor and liquid saturation for different cell sizes. By comparing the Klinkenberg model with different tangential momentum accommodation coefficient (TMAC) values to the Maxwell-Stefan model during primary production, it is possible to select a value of TMAC that can match closely the recovery values of lighter components when using the Maxwell-Stefan equations. However, for heavier hydrocarbon fractions, difference in recovery is more accentuated owing to increased molecule size (more molecular friction). This results in differences in condensate yield during primary production that may be relevant in a field scale. In the cyclic injection scheme, the importance of accounting for frictional effects between molecules is demonstrated using the Maxwell-Stefan formulation. In this case, molecular diffusion fluxes are influenced by high composition gradients. This results in differences between the Maxwell-Stefan and Klinkenberg models in terms of gas stored and hydrocarbon produced during cyclic injection simulations. Furthermore, a sensitivity study on operational parameters in the cyclic injection stage demonstrated that increasing the length of production cycles may be more beneficial than increasing the length of injection or soaking cycles. For the simulations in this study, the gas is injected above the dewpoint and pressure diffusivity is at least one order of magnitude higher than the other physics present in the process. Therefore, increasing the length of production cycles allows for recovery of heavier hydrocarbon fractions that remain in the gas phase. In this work, it is demonstrated that using a rigorous mass transfer formulation, such as the Maxwell-Stefan equations, can provide more information on a per component basis when evaluating cyclic injection schemes in tight condensate reservoirs.
A multimodal data analysis approach for social media during natural disasters
Authors: zhang mengna , huang qisong 
Published: March 2022

Abstract

During natural disaster, social media can provide real-time or low delayed disaster perception information to help government managers carry out disaster response efforts efficiently,therefore, it is of great significance to mining social media information accurately. Distinguished from previous studies, this study proposed a multi-modal data classification model for mining social media information. This model conducted LDA(Late Dirichlet Allocation) to identify subject information from multi-modal data and then analyzed by Bert (bidirectional encoder representation from transformers) and Vgg-16 (visual geometry group 16), text data and image data were classified separately, resulting in real mining of topic information during disasters. This paper used Weibo data during the 2021 Henan heavy storm as the research object, comparing with previous data experiment results, this study proposed a model that can make natural disaster related topic classification of social media data more accurately, resulting in a real-time understanding of different themed natural disasters, it was helpful in making disastrous decisions.
Application Of Iced Normal Saline Combined With Cocktail Perfusion In Total Knee Arthroplasty: Randomized Controlled Trial
Authors: Sui Laijian , Jiang Aihua , Gai Pengzhou , Qi Xiaojun , Wang Jinwei , Wang Jing , Wang Xiufeng , Wang Guangda 
Published: March 2022

Abstract
Trial design: The present study was designed to investigate the safety and effectiveness of iced normal saline combined with cocktail perfusion during total knee arthroplasty (TKA). This was a random, double-blind, parallel-group study conducted in China. Methods: Seventy patients undergoing unilateral total knee replacements were assessed in the present study. Among them, sixty patients with confirmed primary knee osteoarthritis in stage IV were recruited and divided into three groups randomly, three different intro-operative articular cavity perfusion treatments were given according to the randomized and controlled rule. One way ANOVA analysis on visual analogue scale (VAS) score, functional recovery, drainage, and edema of the affected limb were performed to assess the efficiency of the treatment in the following three days after the operation. The participants, care givers, and those assessing the outcomes were blinded to group assignment.Results: Postoperative drainage in group A (n=20) and B (n=20) reduced significantly (P<0.05). The IHC scores of the surgical limbs were markedly lower comparing with the control group (n=20) (P<0.05). No differential postoperative edema was observed and the patient acquired better rehabilitation in group A and B than control group. Compared with group A, no differential postoperative drainage, edema or other side effects were seen in group B (P>0.05). The VAS score of group B was significantly lower than in group A(P<0.05). Postoperative recovery of the surgical limb function in group B was better than in group A (P<0.05).Conclusions: Intra-operation articular cavity perfusion therapy with iced normal saline combined with cocktail perfusion therapy can greatly reduce the early inflammation, contributing to the better rehabilitation of TKA.Trial registration: The present study was retrospectively registered on ClinicalTrials. Gov with the identifier NCT05204056 (27/11/2021).
miRNA-92a Inhibits the Phenotypic Modulation of Vascular Smooth Muscle Cells and May Help to Prevent In-Stent Restenosis
Authors: Jiang Fenfen , Zhang Bin , Deng Lang , Zhang Xiangyu , Zhang Ran , Lu Qin , Shi Fengjie , Xu Jianjiang 
Published: March 2022

Abstract
The modulation of the phenotype of vascular smooth muscle cells (VSMCs) during cell proliferation and migration may represent a potential therapeutic approach for the prevention of vascular intimal hyperplasia. However, the precise role of this process in the biology and remodeling of VSMCs remains unclear. Herein, we demonstrate that miR-92a modulates VSMCs to a synthetic phenotype via the KLF4 pathway. Targeting miR-92a in VSMCs with a KLF4 inhibitor suppressed the synthetic phenotype and inhibited the proliferation and migration of VSMCs. To provide definitive evidence, we measured the expression levels of miR-92a in patients undergoing coronary artery intervention; serum miR-92a levels were significantly higher in patients with In-stent restenosis (ISR) than in those without ISR; these findings were the opposite of those obtained for KLF4. Bioinformatics analysis and promoter-luciferase reporter assays were used to examine the regulatory mechanisms underlying KLF4 expression; we found that KLF4 was transcriptionally upregulated by miR-92a in VSMCs. miRNA transfection was also performed to regulate the expression of miR-92a e. We found that the overexpression of miR-92a inhibited the proliferation and migration of VSMCs and also increased differentiated gene and protein expression. Finally, we found that the inhibition of miR-92a promoted the proliferation and migration of VSMCs; this could be reversed by applying a KLF4 inhibitor. Collectively, these results indicate that the local delivery of a KLF4 inhibitor may act as a novel therapeutic option to prevent in-stent restenosis.
Diffraction-engineered holography: Beyond the coherent limits of holographic displays
Authors: Yang Daeho , Seo Wontaek , Yu Hyeonseung , Kim Sun Il , Shin Bongsu , Lee Chang-Kun , Moon Seokil , An Jungkwuen , Hong Jong-Young , Sung Geeyoung , Lee Hong-Seok 
Published: March 2022

Abstract
Holography is considered as one of the most prominent approaches to realize true-to-life reconstructions of objects. However, owing to the limited resolution compared to static holograms, state-of-the-art computer generated holograms with dynamic display capabilities reconstruct objects exhibiting various coherent properties, such as interference-induced noise and content-dependent defocus blur. Since real world scenes are composed of incoherent light, the coherent properties of reconstructed scenes severely distort the depth perception. Here, we propose a diffraction-engineered hologram, which imitates real world incoherent light by adopting a multi-plane hologram, thereby offering a real world-like defocus blur and a photorealistic reconstruction. Our hologram is synthesized by optimizing a wave field to reconstruct numerous varifocal images after propagating the corresponding focal distances where the varifocal images are rendered using a physically-based renderer. By explicitly adopting out-of-focus images as the optimum intensities, the hologram can be synthesized to reconstruct the scene with the correct defocus blur. Moreover, to reduce the computational costs associated with rendering and optimizing, we also demonstrate a network-based synthetic method that requires only an RGB-D image. We experimentally confirm the incoherent-like depth expression of the hologram, while successfully suppressing unnecessary interference in the reconstructed hologram. Our diffraction-engineered hologram offers comparable synthetic time to previously reported methods while presenting significantly more accurate depth cues, moving one step further to reconstructing naturalistic scenes of a virtual world.
Osteoperiosteal Decortication And Bone Grafting Combined With Wave Plating For Treating Femoral Shaft Aseptic Atrophic Nonunion After Intramedullary Nailing
Authors: Lu Yao , Ren Cheng , Xu Yibo , Sun Liang , Wang Qian , Ye Haobo , Li Ming , Xue Hanzhong , Huang Qiang , Li Zhong , Ma Teng , Zhang Kun 
Published: March 2022

Abstract
Introduction: Nonunion of the femoral shaft after intramedullary nailing fixation remains a challenge for orthopedic surgeons. This study aimed to evaluate osteoperiosteal decortication and iliac bone graft combined with wave plating for treating femoral shaft aseptic atrophic nonunion after intramedullary nailing.Methods: This retrospective study included 22 patients (2 women, 20 men with a mean age of 40.8 years [range, 19–61 years]) with femoral shaft aseptic atrophic nonunion that were treated with osteoperiosteal decortication and iliac bone graft combined with wave plating between January 2016 and January 2020. Cases of infected nonunion, hypertrophic nonunion, and nonunion after plate osteosynthesis were excluded. The clinical outcomes were assessed by the Samantha radiographic grading scale and the Paley scale.Results: The mean follow-up period was 18.8 months (range, 12–35 months). Bone union was achieved in 22 patients. Union was achieved eventually in two cases. The average clinical healing time for nonunion was 5.7 months (range, 3–14 months). The mean Samantha X-ray score was 5.7 ± 0.45. All patients showed excellent and good clinical results (Paley). One patient developed a superficial infection that was cured after a dressing change. Conclusions: Osteoperiosteal decortication and bone graft combined with wave plating is an excellent method for treating femoral shaft aseptic atrophic nonunion after intramedullary nailing.
Learning Ostensive Knowledge of Shaft Parts based on CRF model
Authors: Xiong Wei , LI Haolin 
Published: March 2022

Abstract
During the process of mechanical design, there exit a large amount of knowledge and information that needs to be obtained by consulting and referencing past cases. This type of knowledge is called ostensive knowledge in philosophy, and belongs to a typical relational tacit knowledge. On the one hand, ostensive knowledge cannot be expressed through words, numbers, scientific formulas, and coding procedures. On the other hand, knowledge is parasitic in cases and cannot exist independently from them. This paper introduces ostensive knowledge to the mechanical design field for the first time, and points out that the learning model of ostensive knowledge must have the memories of cases and the ability of case-based reasoning. On this basis, this paper focuses on the shaft parts, and proposes an ostensive knowledge learning model for shaft parts based on the conditional random field model. Finally, an experiment is carried out using actual engineering cases to analyze and verify the model, which shows that the model has good memory and reasoning capabilities for shaft parts cases.
A New Feature Selection Method Based on Frequent and Associated Itemsets For Text Classification
Authors: Farghaly Heba Mamdouh , El-Hafeez Tarek Abd 
Published: March 2022

Abstract
Feature selection is one of the major issues in pattern recognition. The quality of selected features is important for classification as the low-quality data can degrade the model construction performance. Due to the difficulty of dealing with the problem that selected features always contain redundant information, this paper focuses on the association analysis theory in data mining to select important features. In this study, a novel Feature Selection method based on Frequent and Associated Itemsets (FS-FAI) for text classification is proposed. FS-FAI seeks to find relevant features and also takes feature interaction into account. Moreover, it uses association as a metric to evaluate the relativity between the target concept and feature(s). To evaluate the efficacy of the proposed method, several experiments were conducted on a BBC data set from the BBC news website. The obtained results were compared to well-known feature selection methods. The reported results demonstrated the effectiveness of the proposed feature selection method in selecting high-quality features and in handling redundant information in text classification.
Exploiting graph neural network with one-shot learning for fault diagnosis of rotating machinery (PHM2021)
Authors: Yang Shuai , Chen Xu , Bai Yun , Pu Ziqiang 
Published: March 2022

Abstract

Due to lack of training samples, overfitting is a severe problem in fault diagnosis for mechanical devices, especially for rotating machinery. In this paper, a graph neural network (GNN) method with one-shot learning is proposed for fault diagnosis of rotating machinery. Convolutional Neural Network (CNN) is applied to extract the feature vectors and generate codes for one-shot learning. With adjacency matrix in GNN, the proposed method can achieve fault classification for rotating machinery with small dataset. Rotate vector (RV) reducer of the industrial robot and bearing of the rotating shaft were chosen as experimental subjects. Experimental results show the high accuracy of classification in both experiments with the proposed method. To further verify the efficiency of this method, Siamese Net, Matching Net and SAE+RF were chosen as the comparisons. The results indicate the proposed method outperforms all the selected methods for fault classification in both rotating machineries.