bluuebunny/crossref_metadata_2025_split huggingface dataset:
Structural, electronic, and mechanical properties of anatase titanium dioxide
Authors: Dash Debashish , Pandey Chandan Kumar , Chaudhary Saurabh , Tripathy Susanta Kumar 
Published: November 2018

PurposeThe purpose of this paper is to analyze various properties of anatase titanium dioxide (TiO2) nanoparticles. Further, it proposes to implement Linear Combinations of Atomic Orbitals (LCAO) basis set under the framework of density functional theory and outline how LCAO is able to provide improved results in terms of various mechanical properties rather than plane wave and other theoretical results.Design/methodology/approachThis paper provides an exploratory study on anatase TiO2by implementing OLCAO–DFT–LDA–LBFGS–EOS–PZ algorithms to find out various ground-level properties. The data so obtained are complemented by various analysis using mathematical expressions, description of internal processes occurred and comparison to others’ analytical results.FindingsThe paper provides some empirical insights on how mechanical properties of anatase TiO2improved by implementing LCAO methodology. From the analysis of electronic properties, it is seen that the anatase TiO2supports the inter band indirect transition from O-2p in valence region to Ti-3d in the conduction region.Research limitations/implicationsMost of the electronic properties are underestimated because a single exchange-correlation potential is not continuous across the gap. This gap can be enhanced by implementing Green’s function in place of DFT and the other way is to implement self-interaction correction.Practical implicationsThe use of anatase TiO2is primarily used for catalytic applications. This is also used to enhance the quality of paper in the paper industry. Additionally, this is used as a prime ingredient in cosmetic industry.Originality/valueThis paper fulfills an identified need to study how LCAO, another basis set, plays an important role in improving material properties.
Re-modified quintic B-spline collocation method for the solution of Kuramoto–Sivashinsky type equations
Authors: Dhiman Neeraj , Tamsir Mohammad 
Published: November 2018

PurposeThe purpose of this paper is to present a new method, namely, “Re-modified quintic B-spline collocation method” to solve the Kuramoto–Sivashinsky (KS) type equations. In this method, re-modified quintic B-spline functions and the Crank–Nicolson formulation is used for space and time integration, respectively. Five examples are considered to test out the efficiency and accuracy of the method. The main objective is to develop a method which gives more accurate results and reduces the computational cost so that the authors require less memory storage.Design/methodology/approachA new collocation technique is developed to solve the KS type equations. In this technique, quintic B-spline basis functions are re-modified and used to integrate the space derivatives while time derivative is discretized by using Crank–Nicolson formulation. The discretization yields systems of linear equations, which are solved by using Gauss elimination method with partial pivoting.FindingsFive examples are considered to test out the efficiency and accuracy of the method. Finally, the present study summarizes the following outcomes: first, the computational cost of the proposed method is the less than quintic B-spline collocation method. Second, the present method produces better results than those obtained by Lattice Boltzmann method (Lai and Ma, 2009), quintic B-spline collocation method (Mittal and Arora, 2010), quintic B-spline differential quadrature method (DQM) (Mittal and Dahiya, 2017), extended modified cubic B-spline DQM (Tamsir et al., 2016) and modified cubic B-splines collocation method (Mittal and Jain, 2012).Originality/valueThe method presented in this paper is new to best of the authors’ knowledge. This work is the original work of authors and the manuscript is not submitted anywhere else for publication.
Discrimination of the Sicilian Prickly Pear (Opuntia Ficus‐Indica L., CV. Muscaredda) According to the Provenance by Testing Unsupervised and Supervised Chemometrics
Authors: Albergamo Ambrogina , Mottese Antonio F. , Bua Giuseppe D. , Caridi Francesco , Sabatino Giuseppe , Barrega Luna , Costa Rosaria , Dugo Giacomo 
Published: November 2018

AbstractDifferent multivariate techniques were tested in an attempt to build up a statistical model for predicting the origin of prickly pears (Opuntia ficus‐indica L., cv. Muscaredda) from several localities within the Sicilian region. Specifically, two areas known for producing fruits marked respectively by TAP (traditional agri‐food product) and PDO (protected designation of origin) brands, and three sites producing non‐branded fruits, were considered. A validated inductively coupled plasma mass spectrometry (ICP‐MS) method allowed to obtain elemental fingerprints of prickly pears, which were subsequently elaborated by unsupervised tools, such as hierarchical clustering analysis (HCA) and principal component analysis (PCA), and supervised techniques, such as stepwise‐canonical discriminant analysis (CDA) and partial least squares—discriminant analysis (PLS‐DA). With the exception of HCA, which was not enough powerful to correctly cluster all selected samples, PCA successfully investigated the effect of subregional provenance on prickly pears, thus, differentiating labeled products from the non‐labeled counterpart. Also, stepwise CDA and PLS‐DA allowed to build up reliable models able to correctly classify 100% of fruits on the basis of the production areas, by exploiting a restricted pool of metals. Both statistical models, including unsupervised (PCA) and supervised techniques (stepwise CDA or PLS‐DA), may guarantee the provenance of prickly pears protected by quality labels and safeguard producers and consumers.Practical ApplicationBased on elemental analysis and chemometrics, the reliable traceability models herein proposed, could be applied to commercial Sicilian prickly pears protected by TAP and PDO logos to guarantee their provenance and, at the same time, to safeguard producers and consumers.
Prevalence of ROS1 fusion in Chinese patients with non‐small cell lung cancer
Authors: Zhang Qing , Wu Chunyan , Ding Wei , Zhang Zhihong , Qiu Xueshan , Mu Dianbin , Zhang Haiqing , Xi Yanfeng , Zhou Jianhua , Ma Liheng , Fu Shijun , Gao Min , Wang Bo , Deng Juan , Lin Dongmei , Zhang Jie 
Published: November 2018

BackgroundThe study was conducted to investigate the clinicopathological features and prevalence of ROS1 gene fusion in Chinese patients with non‐small cell lung cancer (NSCLC).MethodsThe presence of ROS1 fusion was assessed by quantitative real‐time PCR. Associations between ROS1 fusion and clinical characteristics were analyzed.ResultsIn total, 6066 patients with pathologically confirmed NSCLC and ROS1 fusion test results were enrolled. The average age was 60.89 ± 10.60 years and fusion was detected in 157 (2.59%) patients. Fusion frequency was significantly correlated with age, gender, smoking status (all P < 0.001), pathology type (P = 0.017), and lymph node metastasis stage (P = 0.027). ROS1 fusion‐positive patients were significantly younger (55.68 ± 11.34 vs. negative 61.02 ± 10.44 years; P < 0.01). Fusion frequency was higher in women (3.71% vs. men 1.81%), never‐smokers (3.33% vs. smokers 1.21%), and patients with adenocarcinoma (2.77% vs. squamous lung cancer 0.93%) and at advanced node stages (1.31%, 1.40%, 2.07%, and 3.23% for N0, N1, N2, and N3, respectively). No significant correlation between ROS1 fusion status and pathological stage was found in subgroups classified by pathological, tumor, or metastasis stage (P > 0.05). Age, smoking status, and lymph node stage were statistically significantly correlated with ROS1 fusion frequency (all P < 0.05); gender and pathology type were not significantly correlated with ROS1 fusion status after adjusting for smoking status.ConclusionAn overall ROS1 fusion frequency of 2.59% was confirmed in this study. ROS1 fusion was more prevalent among younger patients, never‐smokers, and those at advanced node stages.
Rapamycin improves healthspan but not inflammaging in nfκb1−/− mice
Authors: Correia‐Melo Clara , Birch Jodie , Fielder Edward , Rahmatika Dina , Taylor Jennifer , Chapman James , Lagnado Anthony , Carroll Bernadette M. , Miwa Satomi , Richardson Gavin , Jurk Diana , Oakley Fiona , Mann Jelena , Mann Derek A. , Korolchuk Viktor I. , Passos João F. 
Published: November 2018

AbstractIncreased activation of the major pro‐inflammatory NF‐κB pathway leads to numerous age‐related diseases, including chronic liver disease (CLD). Rapamycin, an inhibitor of mTOR, extends lifespan and healthspan, potentially via suppression of inflammaging, a process which is partially dependent on NF‐κB signalling. However, it is unknown if rapamycin has beneficial effects in the context of compromised NF‐κB signalling, such as that which occurs in several age‐related chronic diseases. In this study, we investigated whether rapamycin could ameliorate age‐associated phenotypes in a mouse model of genetically enhanced NF‐κB activity (nfκb1−/−) characterized by low‐grade chronic inflammation, accelerated aging and CLD. We found that, despite showing no beneficial effects in lifespan and inflammaging, rapamycin reduced frailty and improved long‐term memory, neuromuscular coordination and tissue architecture. Importantly, markers of cellular senescence, a known driver of age‐related pathology, were alleviated in rapamycin‐fed animals. Our results indicate that, in conditions of genetically enhanced NF‐κB, rapamycin delays aging phenotypes and improves healthspan uncoupled from its role as a suppressor of inflammation.
Spotted wing drosophila (Drosophila suzukii) utilization and dispersal from the wild host Asian bush honeysuckle (Lonicera spp.)
Authors: Leach Heather , Hagler James R. , Machtley Scott A. , Isaacs Rufus 
Published: November 2018

Abstract
Wild host plants in the landscape surrounding fruit farms may significantly influence the movement and population of the polyphagous and invasive pest Drosophila suzukii.
Across 2 years, we sampled wild hosts adjacent to 10 blueberry farms in Michigan, U.S.A. We found five commonly infested wild fruits.
Honeysuckle was a particularly abundant early season reproductive host. Consequently, six blueberry farms with honeysuckle at the margin were evaluated further. At each farm, nonhost plants and honeysuckle were monitored for larval and adult D. suzukii. The season‐long abundance of D. suzukii adults and early‐season infestation was highest near and within honeysuckle.
In 2017, we tracked the movement of D. suzukii between honeysuckle and blueberries in early and late season using a protein immunomarking technique. Of the 1881 flies captured in our study, 7.1% were marked and their distribution pattern was even throughout the farm. Moreover, early season flies were less likely to remain in the marked host compared with late season flies.
The findings of the present study highlight the importance of wild hosts on local pest pressure from D. suzukii and suggest that wild host management should be considered as part of integrated strategies for reducing the economic impacts of this pest.
Prevalence and correlates of growth failure in young African patients with sickle cell disease
Authors: Alexandre‐Heymann Laure , Dubert Marie , Diallo Dapa A. , Diop Saliou , Tolo Aissata , Belinga Suzanne , Sanogo Ibrahima , Diagne Ibrahima , Wamba Guillaume , Boidy Kouakou , Ly Indou Deme , Kamara Ismaël , Traore Youssouf , Offredo Lucile , Jouven Xavier , Ranque Brigitte 
Published: November 2018

SummaryGrowth failure (GF) in children with sickle cell disease (SCD) tends to decline in high‐income countries, but data are lacking in sub‐Saharan Africa. We performed a cross‐sectional study nested in the CADRE (Cœur, Artères et DREpanocytose) cohort in Mali, Senegal, Cameroon, Gabon and the Ivory Coast. SCD patients and healthy controls aged 5–21 years old were recruited (n = 2583). Frequency of GF, defined as a height, weight or body mass index below the 5th percentile on World health Organization growth charts, was calculated. We assessed associations between GF and SCD phenotypic group, clinical and biological characteristics and history of SCD‐related complications. GF was diagnosed in 51% of HbSS, 58% of HbSβ0, 44% of HbSC, 38% of HbSβ+ patients and 32% of controls. GF in patients was positively associated with parents’ lower education level, male sex, age 12–14 years, lower blood pressure, HbSS or HbSβ0 phenotypes, icterus, lower haemoglobin level, higher leucocyte count and microalbuminuria. No association was found between GF and clinical SCD‐related complications. In sub‐Saharan Africa, GF is still frequent in children with SCD, especially in males and during adolescence. GF is associated with haemolysis and microalbuminuria, but not with the history of SCD‐related clinical complications.
Persistent restoration to the immunosupportive tumor microenvironment in glioblastoma by bevacizumab
Authors: Tamura Ryota , Tanaka Toshihide , Ohara Kentaro , Miyake Keisuke , Morimoto Yukina , Yamamoto Yohei , Kanai Ryuichi , Akasaki Yasuharu , Murayama Yuichi , Tamiya Takashi , Yoshida Kazunari , Sasaki Hikaru 
Published: November 2018

Although vascular endothelial growth factor (VEGF) promotes the immunosuppressive microenvironment, the efficacy of bevacizumab (Bev) on tumor immunity has not been fully investigated. The present study used 47 glioblastoma tissues obtained at 3 different settings: tumors of initial resection (naïve Bev group), tumors resected following Bev therapy (effective Bev group), and recurrent tumors after Bev therapy (refractory Bev group). The paired samples of the initial and post‐Bev recurrent tumors from 9 patients were included. The expression of programmed cell death‐1 (PD‐1)/PD ligand‐1 (PD‐L1), CD3, CD8, Foxp3, and CD163 was analyzed by immunohistochemistry. The PD‐L1+ tumor cells significantly decreased in the effective or refractory Bev group compared with the naïve Bev group (P < .01 for each). The PD‐1+ cells significantly decreased in the effective or refractory Bev group compared with the naïve Bev group (P < .01 for each). The amount of CD3+ and CD8+ T cell infiltration increased in the refractory Bev group compared with the naïve Bev group (CD3, P < .01; CD8, P = .06). Both Foxp3+ regulatory T cells and CD163+ tumor‐associated macrophages significantly decreased in the effective or refractory Bev group compared with the naïve Bev group (Foxp3, P < .01 for each; CD163, P < .01 for each). These findings were largely confirmed by comparing paired initial and post‐Bev recurrent tumors. Bevacizumab restores the immunosupportive tumor microenvironment in glioblastomas, and this effect persists during long‐term Bev therapy.
A rapid method for estimation of the efficacy of potential antimicrobials in humans and animals by agar diffusion assay
Authors: Salina Elena G. , Ekins Sean , Makarov Vadim A. 
Published: November 2018

AbstractDrug resistance continues to challenge traditional antimicrobial drugs and limit their clinical utility. This requires us to continue our search for new drug candidates with novel mechanisms of action against infectious diseases. We now describe a simple agar diffusion assay, which can be used as a general method for the rapid detection of antimicrobial activity of drug candidates in animal or human blood plasma for the ultimate prediction of the efficacy of potential drugs prior to clinical trials. We present an example for a clinical candidate against Mycobacterium tuberculosis.
A general model for fuzzy decision tree and fuzzy random forest
Authors: Zheng Hui , He Jing , Zhang Yanchun , Huang Guangyan , Zhang Zhenjiang , Liu Qing 
Published: November 2018

AbstractThe problem of risk classification and prediction, an essential research direction, aiming to identify and predict risks for various applications, has been researched in this paper. To identify and predict risks, numerous researchers build models on discovering hidden information of a label (positive credit or negative credit). Fuzzy logic is robust in dealing with ambiguous data and, thus, benefits the problem of classification and prediction. However, the way to apply fuzzy logic optimally depends on the characteristics of the data and the objectives, and it is extraordinarily tricky to find such a way. This paper, therefore, proposes a general membership function model for fuzzy sets (GMFMFS) in the fuzzy decision tree and extend it to the fuzzy random forest method. The proposed methods can be applied to identify and predict the credit risks with almost optimal fuzzy sets. In addition, we analyze the feasibility of our GMFMFS and prove our GMFMFS‐based linear membership function can be extended to a nonlinear membership function without a significant increase in computing complex. Our GMFMFS‐based fuzzy decision tree is tested with a real dataset of US credit, Susy dataset of UCI, and synthetic datasets of big data. The results of experiments further demonstrate the effectiveness and potential of our GMFMFS‐based fuzzy decision tree with linear membership function and nonlinear membership function.
Spatial variability in the somatic growth of pikeperch Sander lucioperca, an invasive piscivorous fish
Authors: Nolan Emma T. , Britton J. Robert 
Published: November 2018

AbstractIntroduced fishes can develop invasive populations that impact native species and ecosystems. Understanding the population ecology of introduced species in their extended ranges and how this compares to their native ranges is therefore important for informing their management. Here, the age and somatic growth rates of the piscivorous freshwater fish pikeperch Sander lucioperca were analysed across their invasive and native ranges to determine their spatial patterns and drivers. Analyses were initially completed in their invaded range in central and western England. Populations varied spatially in their growth rates; being slowest for a population in a narrow and shallow canal and fastest in a large, impounded lowland river. A meta‐analysis of parameters of the von Bertalanffy growth model then revealed that across their native and invasive ranges, their theoretical ultimate lengths (L∞) and growth coefficients (K) were significantly related to latitude, but not longitude. Their relationships with latitude were nonlinear, with higher values of L∞ and lower values of K being evident towards their northerly and southerly range limits. Faster growth rates were evident in the middle of their range (45 to 55°N), suggesting temperatures here were most optimal for growth, but were in a trade‐off with reduced ultimate lengths. These spatial patterns suggest that whilst introduced S. lucioperca can colonise new waters across a wide area, the expression of their life‐history traits will vary spatially, with potential implications for how invasive populations establish and integrate into native fish communities.
Experimental study of unstable crack propagation velocity for X80 pipeline steel
Authors: Dong Shaohua , Zhang Lai bin , Zhang Hewei , Chen Yinuo , Zhang Hang 
Published: November 2018

AbstractUnstable crack propagation velocity following the failure of pipeline steel has always been a problem. In this study, differences between the existing unstable crack propagation calculation models were analysed, and the deficiencies within the crack propagation velocity models were overcome. The hardening coefficient and hardening index of the ductile material were considered, and a velocity model of unstable crack propagation of pipelines based on the Hutchinson‐Rice‐Rosengren (HRR) theory elastic‐plastic stress‐strain field and the displacement field was established. Consequently, the limit propagation velocity was obtained. In full‐scale burst test, the pipe with diameter of 1422 mm was chosen to simulate the natural gas pipeline transportation environment. Compared with the theoretical result, the error was limited in 13%. The research result solved the problem of quantifying the propagation velocity of the crack in X80 pipeline, which was significant for describing the forecast of velocity and length of unstable propagation and failure characteristics of pipelines.
Methodology for assessment of statistical planning effects on the S‐N curve determination using Monte Carlo simulations
Authors: Goedel Fábio , Chamberlain Pravia Zacarias Martin , Mezzomo Gustavo Prates 
Published: November 2018

AbstractOne of the most important input data in fatigue analysis is the material fatigue properties. This research aims to present a methodology for assessment of statistical planning of fatigue experiments through a MatLab algorithm developed based on Monte Carlo simulations, which enables to simulate statistically the effects of main parameters used for defining the fatigue test setting and to verify their impact on the relative percentage difference (RPD) in fatigue properties estimation comparing to a reference material. The aspects treated here have not been clearly discussed in the standards. Therefore, the proposed recommendations combined with standards procedures is a tool for test engineers, permitting a fatigue test planning with more background and precision, which can help in decisions about which is the better setup, including the sample size, number of stress levels, stress value in each level, and replication. The methodology and good practices presented in this paper were demonstrated by means of actual data from the literature.
Gliomasphere marker combinatorics: multidimensional flow cytometry detects CD44+/CD133+/ITGA6+/CD36+ signature
Authors: Erhart Friedrich , Blauensteiner Bernadette , Zirkovits Gabriel , Printz Dieter , Soukup Klara , Klingenbrunner Simone , Fischhuber Katrin , Reitermaier René , Halfmann Angela , Lötsch Daniela , Spiegl‐Kreinecker Sabine , Berger Walter , Visus Carmen , Dohnal Alexander 
Published: November 2018

AbstractGlioblastoma is the most dangerous brain cancer. One reason for glioblastoma's aggressiveness are glioblastoma stem‐like cells. To target them, a number of markers have been proposed (CD133, CD44, CD15, A2B5, CD36, CXCR4, IL6R, L1CAM, and ITGA6). A comprehensive study of co‐expression patterns of them has, however, not been performed so far. Here, we mapped the multidimensional co‐expression profile of these stemness‐associated molecules. Gliomaspheres – an established model of glioblastoma stem‐like cells – were used. Seven different gliomasphere systems were subjected to multicolor flow cytometry measuring the nine markers CD133, CD44, CD15, A2B5, CD36, CXCR4, IL6R, L1CAM, and ITGA6 all simultaneously based on a novel 9‐marker multicolor panel developed for this study. The viSNE dimensionality reduction algorithm was applied for analysis. All gliomaspheres were found to express at least five different glioblastoma stem‐like cell markers. Multi‐dimensional analysis showed that all studied gliomaspheres consistently harbored a cell population positive for the molecular signature CD44+/CD133+/ITGA6+/CD36+. Glioblastoma patients with an enrichment of this combination had a significantly worse survival outcome when analyzing the two largest available The Cancer Genome Atlas datasets (MIT/Harvard Affymetrix: P = 0.0015, University of North Carolina Agilent: P = 0.0322). In sum, we detected a previously unknown marker combination – demonstrating feasibility, usefulness, and importance of high‐dimensional gliomasphere marker combinatorics.