bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of Landslide Susceptibility of the Ya'an-Linzhi Section of the Sichuan-Tibet Railway based on Deep Learning
Authors: Shibao Wang , Zhuang Jianqi , Jiaqi Mu , Jia Zheng , Jiewei Zhan , Jie Wang , Yuting Fu 
Published: August 2021

Abstract
The Qinghai-Tibet Plateau is one area with the most frequent landslide hazards due to its unique geology, topography, and climate conditions, posing severe threats to engineering construction and human settlements. The Sichuan-Tibet Railway that is currently under construction crosses the Qinghai-Tibet Plateau; there are frequent landslide disasters along the line, which seriously threaten the construction of the railway. This paper applied two deep learning (DL) algorithms, the convolutional neural network (CNN) and deep neural network (DNN), to landslide susceptibility mapping of the Ya’an-Linzhi section of the Sichuan-Tibet Railway. A geospatial database was generated based on 587 landslide hazards determined by Interferometric Synthetic Aperture Radar (InSAR) Stacking technology, field geological hazard surveys, and 18 landslide influencing factors were selected. The landslides were randomly divided into training data (70%) and validation data (30%) for the modeling training and testing. The Pearson correlation coefficient and information gain method were used to perform the correlation analysis and feature selection of 18 influencing factors. Both models were evaluated and compared using the receiver operating characteristic (ROC) curve and confusion matrix. The results show that better performance in both the training and testing phases was provided by the CNN algorithm (AUC = 0.88) compared to the DNN algorithm (AUC = 0.84). Slope, elevation, and rainfall are the main factors affecting the occurrence of landslides, and the high and very high landslide susceptibilities were primarily distributed in the Jinsha, Lancang, and Nujiang River Basins along the railway. The research results provide a scientific basis for the construction of the Ya'an-Linzhi section of the Sichuan-Tibet Railway within the region, as well as the disaster prevention and mitigation work during future safe operations.
Application of Two Level Count Regression Modeling on the Determinants of Fertility among Married Women in Ethiopia
Authors: Hussen Nuru Mohammed 
Published: August 2021

Abstract
Background: Fertility is the element of population dynamics that has a vital contribution towards changing population size and structure over time. The global population showed a major increment from time to time because of these dynamics, particularly in south Asia and sub-Saharan Africa including Ethiopia. So this study targeted on the factors affecting fertility among married women in Ethiopia through the framework of multilevel count regression analysis using EDHS 2016 data.Methods: The sampling design for EDHS 2016 was a two-stage stratified cluster sampling design, where stratification was achieved by separating every region into urban and rural areas except the Addis Ababa region. Results: Among the random sample of 6141 women in the country, 27150 births were recorded based on EDHS 2016 report. The histograms showed that the data has a positively skewed distribution extremely picked at the beginning. Two- level negative binomial regression model was fitted to spot out the determinants of fertility among married women in Ethiopia because it has the smallest value for the fit statistics and the variance of the data was higher than its mean.Conclusion: Findings from the study revealed that contraception method used, residence, educational level of women, women’s age at first birth, and proceeding birth interval were the major predictors of fertility among married women in Ethiopia. Moreover, the estimates from the random effect result revealed that there is more fertility variation between the enumeration areas than within the enumeration areas. Application of standard models by ignoring this variation ought to embrace spurious results, then multilevel modeling is recommended for such types of hierarchical data.
Mycofabrication of Silver Oxide Nanoparticles Derived from Aspergillus Terreus FC36AY1 and its Potent Antimicrobial, Antioxidant, and Anti-Angiogenesis Activities
Authors: Vellingiri Manon Mani , Kennedy Mithu Ashwin John , Jeyasundar Parimala Gnana Soundari Arockiam , Sathiskumar Swamiappan , Priyadharshini Ulaganathan , Deepak Paramasivam , Liu Wen-chao , Balasubramanian Balamuralikrishnan 
Published: August 2021

Abstract
The present study focused to synthesize the silver oxide nanoparticles (AgONPs) from endophytic fungus, as the strain eventually possess the medicinal property acquired from the medicinal tree, Aegle marmelos. About 35 pigmented endophytic fungi were isolated, screened for antagonistic activity against 12 clinical human pathogens and antioxidant activity through DPPH radical scavenging assay; among the isolates, FC36AY1 explored the highest activity. The endophytic fungus was identified as Aspergillus terreus FC36AY1 through microscopic and Internal Transcribed Spacer (ITS) 1, ITS 4 and 18S rRNA amplification. The AgONPs were synthesized from the strain FC36AY1 and characterized for its confirmation, functional groups, nanostructures with unit cell dimensions, size and shape, presence of elements through UV-Vis spectrophotometry, FT-IR, X-Ray Diffraction, Scanning Electron Microscopic with EDX analysis. The myco-generated AgONPs manifested their antimicrobial and antioxidant properties with maximum activity at minimum concentration. Moreover, the inhibition of angiogenesis by the AgONPs in Hen’s Egg Test on the Chorio-Allantoic Membrane analysis evinced significant bioactivity at least concentration. Thus the results of this investigation revealed that this bioactive fungal mediated AgONPs can be exploited as potential in biomedical applications.
Association of Cognitive Impairment With Migrant Status Among Older Adults in India: A Cross-Sectional Study
Authors: Srivast Shobhit , Singh Ruchi , Mishra Prem Shankar , Aditya Alok 
Published: August 2021

Abstract
Introduction Among various health implications for older adult, cognitive impairment and related dementias are significant public health concern in many low and middle income countries, including India and lack due attention in policy arena. Socio-economic and health vulnerability are associated with cognitive impairment among older adults. Therefore the present study explores the prevalence and determinants of cognitive impairment among older adults in India with special reference to migrant status of older adults. MethodsData for this study was utilized from recent release of Longitudinal Ageing Study in India (LASI) wave 1 2017-19. The LASI is a nationally representative survey over 72000 older adults age 45 and above across all states and union territories of India. The present study is conducted on the eligible respondent’s age 60 years and above. The total sample size for the present study is 31,464 older adults aged 60 years and above (Male-15,068; Female-16,366). Descriptive and logistic regression analysis carried to fulfil the objective of the study. ResultsOverall, the prevalence of cognitive impairment among male older adults was 6.4% and female older adults 19.8%. Non-migrant status (6.8%) was more likely to face cognitive impairment than migrant status (5.7%) among older adults. The high prevalence of cognitive impairment were found with increasing socio-economic, demographic and multi-morbidities among older adults. Older adults (male 6.7% vs. female 20.2%) with no social participation were more likely to be face cognitive impairment. The result of logistic regression of our study is supported the bivariate analysis. Older adults with migrant status were more likely to be suffered from the cognitive impairment with unadjusted [UOR; 1.57, CI: 1.45-1.70] & after adjusting with covariates [AOR; 1.14, CI: 1.03-1.26] as compared to non-migrant status. Among the individual factors, odds of impairment was very high for the oldest-older adults age group [AOR: 2.95, CI: 2.59-3.36] as compared to young-older adults and further, female older adults were more likelihood to be cognitive impairment [AOR: 1.99, CI: 1.77-2.24] than their counterparts. Similar findings were also found with socio-economic and health vulnerability among older adults.Conclusion The study demonstrates that female older adults need more care and support from community and government as they face higher cognitive impairment. Further, the results significantly varied across different socio-economically, demographically, regionally in cognitive impairment and those who were suffering with co-morbidities. Comprehensive primary health care with community health approach may improve the health status of older adults in later period of life.
Synthesis and Characterization of Epoxidized Silkworm Pupae Oil and Its Application as Polyvinyl Chloride
Authors: Ji Yingrui , Xu Long , Xu Qingqing , Liu Xuan , Lin Sen , Liao Sentai , Wang weifei , Lan Dongming 
Published: August 2021

Abstract
This study aimed to prepare epoxidized silkworm pupae oil (ESPO) and investigate their effects on the thermal stability and plasticization of polyvinyl chloride (PVC) films. A chemo-enzymatic method of ESPO was developed in the presence of Lipase SMG1-F278N and H2O2 in natural deep eutectic solvents (DESs). Lipase SMG1-F278N could initiate the epoxidation reaction effectively at room temperature with a negligible loss of activities 10 batches. A maximum oxirane value of 6.94% was obtained. The formation of oxirane ring in ESPO was confirmed by FT-IR and 13C NMR spectra. Moreover, ESPO showed a better thermal stability and lower freezing point than epoxidized soybean oil (ESO). It was demonstrated that ESPO had a good frost resistance. In addition, ESPO showed a significantly improved plasticizing effect on flexible polyvinyl chloride (PVC). Compared with ESO, ESPO could increase the tensile elongation at break effectively. A significantly lower migration rate of plasticizer was observed in PVC plasticized with ESPO.
Effect of Noni on memory impairment induced by hydrocortisone in mice
Authors: ZHANG RUI , LIU JINLIAN , HOU XINJUAN , ZHAO FAN , WANG CHANDI , ZHU YINGLI , DENG SHIXIN , TANG RUYING , DI SONGRUI , YU SHUHUI , WANG CHUN , ZHANG JIANJUN 
Published: August 2021

Abstract
Background
Oxidative stress and memory impairment have been implicated, a common functional brain disease. Nuclear factor E2-related factor 2 (Nrf2) is highly induced in oxidative stress, indicating that Nrf2 is an emerging target of memory therapy. This study aimed to investigate the effect of Noni on brain memory impairment induced by hydrocortisone and its protection mechanism in mice.
Methods
Male Kuming mice were (n = 8/group) given hydrocortisone by gastric gavage for 14 consecutive days to establish the memory impairment model except for those in the control group. At the same day, the corresponding drugs were given by gastric gavage. The changes in ethology were examined. Brains were extracted and subjected to western blot analysis and biochemical analyses to assess the activities of oxidative stress.
Results
The middle and high-dose Noni groups ameliorated the ethology and the high-dose Noni group increased cerebral protein expressions of Nrf2, kelch-like ECH-associated protein 1 (KEAP1) and heme oxygenase-1 (HO-1), as compared to the model group. The arrangement of CA3 vertebral cells in hippocampus of mice was slightly compact and hyperchromatic and pyknosis were alleviated. Furthermore, the biochemical analyses showed the activities of related enzymes of oxidative stress in high-dose Noni group were increased.
Conclusions
Noni might be a powerful antioxidant that can protect nerve cell and may possess as a potential benefit for the treatment of memory impairment.
Factors Influencing the Improvement of Activities of Daily Living During Inpatient Rehabilitation in Newly Diagnosed Patients with Glioblastoma
Authors: Natsume Keisuke , Sakakima Harutoshi , Kawamura Kentaro , Yoshida Akira , Akihiro Shintaro , Yonezawa Hajime , Yoshimoto Koji , Shimodozono Megumi 
Published: August 2021

Abstract
Purpose

To identify pre-, intra-, and postoperative factors influencing the improvement of the activities of daily living (ADL) in newly diagnosed patients with glioblastoma (GBM), we investigated the characteristics and variable factors and overall survival.
Methods

A total of 105 patients with GBM were retrospectively analyzed and categorized into three groups according to the quartile of change of Barthel index score from admission to discharge: deterioration (n = 25), no remarkable change (n = 55), and good recovery (n = 25). We compared with the characteristics, variable factors, and overall survival of patients with deterioration and good recovery after tumor resection.
Results

There was statistically different in the pre-, intra-, and post-operative factors between the groups. Multiple regression analysis identified four significant predictor variables that may influence the improvement of ADL after surgery: the improvement of motor paralysis after surgery, mild fatigue during chemoradiotherapy, poor Karnofsky performance status at admission, and length up to early walking training onset. The median overall survival was significantly different between the patients with deterioration (10.6 months, 95% CIs, 5.19–16.00) and good recovery (18.9 months, 95% CIs, 8.61–29.18) (p = 0.025).
Conclusion

This study identified four factors influencing the improvement of ADL after surgery. In addition, a structured inpatient rehabilitation programs can be performed safely and improve functional outcomes, which may contribute to the survival prognosis.
Research on Stability of Robotic Longitudinal-Torsional Ultrasonic Milling With Variable Cutting Force Coefficient
Authors: Zhang Jianlong , Zhao Wei , Li Bo , Tian Wei , Zheng Kan , Liao Wenhe 
Published: August 2021

Abstract
With their successful applications in handling, spraying, arc welding and other processing fields, industrial robots are gradually replacing traditional CNC machine tools to complete machining tasks due to the wider working envelope and the higher flexibility. Aiming at the chatter problem, a robotic longitudinal-torsional ultrasonic milling method with variable force coefficient is proposed in this paper. Taking Carbon Fiber Reinforced Plastics (CFRP) as the processing object, the influence of the fiber layup angle on the milling force are analyzed first; then the robot milling force parameters are determined and the robot milling kinematics model is established. Furthermore, the ultrasonic function angle is defined, and the cutting layer thickness model, the dynamic milling force model and the dynamic differential equation under ultrasonic vibration are established to analyze the stability of robotic longitudinal-torsional ultrasonic milling of CFRP. Finally, the full discrete method is used to obtain stability lobe diagrams.
A profile of children’s physical activity data from the 2012 and 2015 Health Survey for England
Authors: Sims Jamie , Milton Karen , Foster Charlie , Scarborough Peter 
Published: August 2021

Abstract
Background

Low childhood physical activity levels constitute an important modifiable risk for adult non-communicable disease incidence and subsequent socio-economic burden, but few publications have explored age and sex related patterns within the UK population. The aims were to profile child physical activity data from the Health Survey for England from 2012 (1,732 respondents) and 2015 (5,346 respondents).
Methods

Reported physical activity episodes were converted to metabolic equivalents with reference to child-specific compendiums. Physical activity levels were aggregated for each domain, and again to produce total physical activity estimates. Contributions from each domain to total physical activity were explored, stratifying for age, sex, socio-economic deprivation, geographical region, ethnicity, and weight status. Further analyses were run stratifying for physical activity levels. Few differences were detected between the survey iterations.
Results

Boys reported higher absolute levels of physical activity at all ages and across all domains. For boys and girls, informal activity reduces with age. For boys this reduction is largely mitigated by increased formal sport, but this is not the case for girls. Absolute levels of school activity and active travel remained consistent regardless of total physical activity, thereby comprising an increasingly important proportion of total physical activity for less active children.
Conclusions

We recommend a specific focus on establishing and maintaining girl’s participation in formal sport thorough their teenage years, and a recognition and consolidation of the important role played by active travel and school-based physical activity for the least active children.
Cellulose Based Electrospun Nanofilters: Perspectives On Tannery Effluent Waste Water Treatment
Authors: Rethinam Senthil , Kavukcu Sardar Batıkan , Hemalatha Thiagarajan , Aruni A.Wilson , Sendemir Aylin 
Published: August 2021

Abstract
Development of nanofilters with the capability to remove toxic metal ions from effluent wastewater will be of immense help to the leather industry. In this study, fibrous nanofilter (FNF) was prepared using micro cellulosic fiber (MCF) and tea leaves microparticles (TLM) blended in poly (vinyl) alcohol (PVA). FNF was analysed for its efficacy to remove hazardous metals from tannery effluent wastewater. The FNF had promising traits of tensile strength (19.24+0.05 Mpa), elongation at break (22.31+0.12 %), flexibility (10.88+0.05 %), water absorption (37.86+0.14 %) and desorption (32.54+0.33 %). The metal adsorption studies clearly reflected the removal of toxic Cr (VI) ions from the effluent water by FNF. The study establishes an economically feasible and highly efficient way to remove hazardous metal ions from effluent wastewater.
Novel exosome biomarker candidates for Alzheimer´s disease unraveled through Mass Spectrometry analysis
Authors: Martins Tânia Soares , Marçalo Rui , Silva Cristóvão B. da Cruz e , Trindade Dário , Catita José , Amado Francisco , Melo Tânia , Rosa Ilka Martins , Vogelgsang Jonathan , Wiltfang Jens , Silva Odete A. B. da Cruz e , Henriques Ana Gabriela 
Published: August 2021

Abstract
Background
Exosomes are small extracellular vesicles (EVs) present in human biofluids that can carry disease-specific molecules. Blood-derived exosomes emerged as interesting peripheral sources of biomarkers for a wide range of diseases, and their potential is also being addressed in Alzheimer’s disease (AD) context. There is no effective cure or blood-based molecular diagnostic tools for a first clinical AD screening, which motivates research in this area to identify putative valuable blood-derived disease biomarkers. The ultimate goal is to produce a cost-effective and widely available alternative to the current molecular AD diagnosis that monitors a biomarker triplet in the CSF.
Methods
In the study here presented, EVs with exosome-like characteristics were isolated from the serum of Controls and AD cases through two distinct methods, precipitation- and column-based methods, followed by mass spectrometry analysis. The resulting proteomes from Controls and AD cases were characterized by Gene Ontology (GO) functional enrichment and multivariate analysis. Putative candidate targets identified were validated in distinct cohorts using antibody-based approaches.
Results
Both methodologies isolated particles with the expected morphology and size range. Although GO terms were similar for Controls and AD cases exosomes in both methodologies, the multivariate analysis revealed a clear segregation between Controls and AD cases obtained by the precipitation method. Nine significantly different abundant proteins were identified between Controls and AD cases and exosome levels of AACT and C4BPα, two Aβ-binding proteins, were validated in individuals from independent cohorts.
Conclusions
Serum-derived exosome proteomes were unraveled for the first time in the context of AD through two distinct isolation methodologies, holding disease discriminatory potential. The work carried out gives an important contribution to the identification of novel exosomal biomarker candidates potentially useful as blood-based tools for AD diagnosis.
Defect Prediction For Assembled Products: A Novel Model Based On The Structural Complexity Paradigm
Authors: Verna Elisa , Genta Gianfranco , Galetto Maurizio , Franceschini Fiorenzo 
Published: August 2021

Abstract
Increased assembly complexity is one of the main challenges in manufacturing. Complexity can induce increased assembly cost and time, operational issues, costly defects and quality losses. Several approaches have been proposed in the literature to predict product defects by using assembly complexity as predictor. Despite defect prediction is of utmost importance from the early stages of product and related quality inspection design, most approaches are not directly applicable because they rely on the operators' prior subjective knowledge and are designed for specific industrial applications. To overcome this issue, the present research proposes a novel approach to predict product defects from a more objective evaluation of complexity. This is one of the first attempts to predict product defects and improve its quality with a purely objective assessment of the complexity of the assembled product, without the need for operators' evaluations and assembly experience. Defect rates in the model are predicted by using a recent conceptual paradigm of complexity that considers only structural properties of assembly parts and their architectural structure. The novel model is applied to a real assembly process in the electromechanical field and is compared with one of the most accredited in the literature, i.e. the Shibata-Su model. Empirical results show that, despite the super-linear relationship between defect rates and complexity in both models, the objective approach used in the novel model leads to more accurate and precise predictions of defectiveness rates, as it does not include the variability introduced by operators' subjective assessments. Adopting this novel model can effectively improve the estimate of product defects and support designers’ decisions for assembly quality-oriented design and optimization, especially in early design phases.