bluuebunny/crossref_metadata_2025_split huggingface dataset:
BIM‐Anwendungsfall (AwF) Abrechnung‐Vortrieb am Beispiel des Zentrums am Berg
Authors: Wenighofer Robert , Waldhart Johannes , Eder Nina , Zach Katharina 
Published: April 2020

AbstractBIM modelling of infrastructure works is controlled by a global market consisting of few software suppliers and is contingent upon the functions provided by them. Customization options furnished by the software suppliers often enable enhancement of functions, which is essential for infrastructure BIM although not completely available. This enables improved interoperability of the software tools used in this area. IFC is most likely to become an established international format for data exchange with its constant but also intricate further development. However, in underground infrastructure construction, both international and national standards are used and the integration of the latter in IFC cannot be anticipated. Hence, the implementation of BIM has to apply national standards in the use cases of collaborative data exchange among the different disciplines in tunnelling. In this contribution, the use case of payment of excavation classes and its implementation in a BIM environment are addressed. It discusses the interoperable interlinkage of software tools commonly used in construction to generate consistent digital data transfer and it underscores the need for an interdisciplinary agreement to integrate national standards into adequate practice for the implementation of BIM.
Cascade degradation of organophosphorus pollutant by photoenzymatic integrated nanocatalyst
Authors: Jiang Yanjun , Guan Sumin , Zhang Ying , Liu Guanhua , Zheng Xiaobing , Gao Jing 
Published: April 2020

AbstractBACKGROUNDAs visible‐light photocatalytic semiconductors, BiOBr‐based catalysts have a promising application prospect for the degradation of dyes and pollutants in wastewater. Enzyme catalysis has become a promising technology in the degradation of organophosphorus pollutants due to excellent activity and specificity. Herein, a photoenzymatic integrated nanocatalyst of organophosphorus hydrolase (OPH) immobilized on BiOBr (OPH@BiOBr) was successfully synthesized for the cascade degradation of methyl parathion under visible light.RESULTSThe obtained OPH@BiOBr could degrade methyl parathion into para‐nitrophenol (p‐NP) by hydrolyzing the PS bond using OPH, and then converting the produced p‐NP into a less toxic substance through photocatalysis of BiOBr. After 3 h of reaction, methyl parathion was degraded into hydroquinone and nearly 80% of the produced p‐NP was further degraded at the same time. The OPH@BiOBr nanocatalyst could be recycled five times and still retained 83% of its initial activity.CONCLUSIONSA novel photoenzymatic integrated nanocatalyst was developed for cascade degradation of methyl parathion under visible light. This represents the first attempt at eliminating pesticide residues by combining enzyme with photocatalyst through a cascade reaction. Considering the fact that wastewater may have pesticide residues, photoenzymatic integrated catalysts will be useful for the degradation of pollutants. The unique flower‐like structure of the nanocatalyst could not only improve photocatalytic activity but also protect enzyme molecules so as to complete the cascade degradation. In addition, with the development of enzyme engineering and photocatalysis, the integrated nanocatalysts that combine photocatalyst with enzyme will have more and more application in the fields of energy and the environment. © 2020 Society of Chemical Industry
Forecasts of ENSO evolution using spatial–temporal projection model
Authors: Pan Xiao , Zhu Zhiwei , Li Tim 
Published: April 2020

AbstractEl Niño–Southern Oscillation (ENSO) prediction is one of the most debated and challenging tasks, whilst its real‐time operational prediction skill still has room for improvement. In this study, spatial–temporal projection model is applied to predict Niño3.4 index at lead time of one to six months. By regressing variable fields onto Niño3.4 index month by month, physical‐based predictability sources, that is, the mixed‐layer oceanic temperature, sea surface temperature, thermocline depth, and accumulated westerly‐wind‐events index over the specific regions are detected as the predictors. Based on the temporal evolution of coupled modes of predictors and Niño3.4 index, the Niño3.4 index from JAS (July, August, and September) to DJF (December, January, and February) can be predicted once a year. The model could nicely reproduce the evolution of Niño3.4 index from JAS to DJF. It also achieved high prediction skills for the year‐to‐year DJF Niño3.4 index, with a root‐mean‐square error of 0.46 in the training period (1950–2000) and 0.52 in the independent‐forecast period (2001–2016). Further investigation shows that the forecast is more reliable when the forecasted ENSO amplitude is much larger.
Covalently bonded aptamer‐functionalised magnetic mesoporous carbon for high‐efficiency chloramphenicol detection
Authors: Zhang Qianchun , Zhou Qingqing , Yang Lu , Wang Xingyi , Zheng Yuguo , Bao Linchun 
Published: April 2020

AbstractA novel aptamer‐modified magnetic mesoporous carbon was prepared to develop a specific and sensitive magnetic solid‐phase extraction method through combination with ultra‐high performance liquid chromatography‐tandem mass spectrometry for the analysis chloramphenicol in complex samples. More specifically, the chloramphenicol aptamer‐modified Mg/Al layered double hydroxide magnetic mesoporous carbon was employed as a novel magnetic solid‐phase extraction sorbent for analyte enrichment and sample clean‐up. The extraction solvent, extraction time, desorption solvent, and desorption time were investigated. It was found that the mesoporous structure and aptamer‐based affinity interactions resulted in acceptable selective recognition and a good chemical stability toward trace amounts of chloramphenicol. Upon combination with the ultra‐high performance liquid chromatography‐tandem mass spectrometry technique, a specific and sensitive recognition method was developed with a low limit of detection (0.94 pmol/L, S/N = 3) for chloramphenicol analysis. The developed method was successfully employed for the determination of chloramphenicol in complex serum, milk powders, fish and chicken samples, giving recoveries of 87.0‐107% with relative standard deviations of 3.1‐9.7%.
Metabolomic‐Based Approach to Identify Biomarkers of Apple Intake
Authors: McNamara Aoife E. , Collins Cassandra , Harsha Pedapati S. C. Sri , González‐Peña Diana , Gibbons Helena , McNulty Breige A. , Nugent Anne P , Walton Janette , Flynn Albert , Brennan Lorraine 
Published: April 2020

ScopeThere is an increased interest in developing biomarkers of food intake to address some of the limitations associated with self‐reported data. The objective is to identify biomarkers of apple intake, examine dose–response relationships, and agreement with self‐reported data.Methods and resultsMetabolomic data from three studies are examined: an acute intervention, a short‐term intervention, and a free‐living cohort study. Fasting and postprandial urine samples are collected for analysis by 1H‐NMR and liquid chromatography–mass spectrometry (LC–MS). Calibration curves are developed to determine apple intake and classify individuals into categories of intake. Multivariate analysis of data reveals that levels of multiple metabolites increase significantly post‐apple consumption, compared to the control food—broccoli. In the dose‐response study, urinary xylose, epicatechin sulfate, and 2,6‐dimethyl‐2‐(2‐hydroxyethyl)‐3,4‐dihydro‐2H‐1‐benzopyran increase as apple intake increases. Urinary xylose concentrations in a free‐living cohort perform poorly at an individual level but are capable of ranking individuals in categories of intake.ConclusionUrinary xylose exhibits a dose–response relationship with apple intake and performs well as a ranking biomarker in the population study. Other potential biomarkers are identified and future work will combine these with xylose in a biomarker panel which may allow for a more objective determination of individual intake.
Learning osteoarthritis imaging biomarkers from bone surface spherical encoding
Authors: Morales Martinez Alejandro , Caliva Francesco , Flament Io , Liu Felix , Lee Jinhee , Cao Peng , Shah Rutwik , Majumdar Sharmila , Pedoia Valentina 
Published: April 2020

PurposeTo learn bone shape features from spherical bone map of knee MRI images using established convolutional neural networks (CNN) and use these features to diagnose and predict osteoarthritis (OA).MethodsA bone segmentation model was trained on 25 manually annotated 3D MRI volumes to segment the femur, tibia, and patella from 47 078 3D MRI volumes. Each bone segmentation was converted to a 3D point cloud and transformed into spherical coordinates. Different fusion strategies were performed to merge spherical maps obtained by each bone. A total of 41 822 merged spherical maps with corresponding Kellgren‐Lawrence grades for radiographic OA were used to train a CNN classifier model to diagnose OA using bone shape learned features. Several OA Diagnosis models were tested and the weights for each trained model were transferred to the OA Incidence models. The OA incidence task consisted of predicting OA from a healthy scan within a range of eight time points, from 1 y to 8 y. The validation performance was compared and the test set performance was reported.ResultsThe OA Diagnosis model had an area‐under‐the‐curve (AUC) of 0.905 on the test set with a sensitivity and specificity of 0.815 and 0.839. The OA Incidence models had an AUC ranging from 0.841 to 0.646 on the test set for the range from 1 y to 8 y.ConclusionBone shape was successfully used as a predictive imaging biomarker for OA. This approach is novel in the field of deep learning applications for musculoskeletal imaging and can be expanded to other OA biomarkers.
Venous cerebral blood volume mapping in the whole brain using venous‐spin‐labeled 3D turbo spin echo
Authors: Lee Hyunyeol , Wehrli Felix W. 
Published: April 2020

PurposeVenous cerebral blood volume (CBVv) is a major contributor to BOLD contrast, and therefore is an important parameter for understanding the underlying mechanism. Here, we propose a velocity‐selective venous spin labeling (VS‐VSL)‐prepared 3D turbo spin echo pulse sequence for whole‐brain baseline CBVv mapping.MethodsUnlike previous CBVv measurement techniques that exploit the interrelationship between BOLD signals and CBVv, in the proposed VS‐VSL technique both arterial blood and cerebrospinal fluid (CSF) signals were suppressed before the VS pulse train for exclusive labeling of venous blood, while a single‐slab 3D turbo spin echo readout was used because of its relative immunity to magnetic field variations. Furthermore, two approximations were made to the VS‐VSL signal model for simplified derivation of CBVv. In vivo studies were performed at 3T field strength in 8 healthy subjects. The performance of the proposed VS‐VSL method in baseline CBVv estimation was first evaluated in comparison to the existing, hyperoxia‐based method. Then, data were also acquired using VS‐VSL under hypercapnic and hyperoxic gas breathing challenges for further validation of the technique.ResultsThe proposed technique yielded physiologically plausible baseline CBVv values, and when compared with the hyperoxia‐based method, showed no statistical difference. Furthermore, data acquired using VS‐VSL yielded average CBVv of 2.89%/1.78%, 3.71%/2.29%, and 2.88%/1.76% for baseline, hypercapnia, and hyperoxia, respectively, in gray/white matter regions. As expected, hyperoxia had negligible effect (P > .8), whereas hypercapnia demonstrated vasodilation (P << .01).ConclusionUpon further validation of the quantification model, the method is expected to have merit for 3D CBVv measurements across the entire brain.
FHITlow/pHER2high signature in non‐small cell lung cancer is predictive of anti‐HER2 molecule efficacy
Authors: Da Silva Jordan , Jouida Amina , Ancel Julien , Dalstein Véronique , Routhier Julie , Delepine Gonzague , Cutrona Jérôme , Jonquet Antoine , Dewolf Maxime , Birembaut Philippe , Deslée Gaëtan , Polette Myriam , Nawrocki‐Raby Béatrice 
Published: April 2020

AbstractDespite its efficacy in solid tumours, in particular HER2+ breast cancer, HER2‐targeted therapy has given rise to disappointing results in non‐small cell lung cancer (NSCLC). With the aim of refining the target population for anti‐HER2 therapies in NSCLC, we investigated the relationships between HER2 and the tumour suppressor fragile histidine triad (FHIT) in lung tumour cells. First, we observed a negative correlation between FHIT expression and the activated form of HER2 (pHER2) in NSCLC samples and in lung tumour cell lines. Moreover, the silencing or overexpression of FHIT in lung cell lines led to an increase or decrease of HER2 activity, respectively. We also demonstrated that two anti‐HER2 drugs, irbinitinib and trastuzumab, restore a more epithelial phenotype and counteract cell invasiveness and growth of FHIT‐silenced tumour cell lines. Finally, we showed that the FHITlow/pHER2high phenotype predicts sensitivity to an anti‐HER2 therapy in primary tumour cells from NSCLC patients. Our results show that FHIT regulates the activity of HER2 in lung tumour cells and that FHIT‐inactivated tumour cells are sensitive to HER2 inhibitors. A new subclass of patients with NSCLC may be eligible for an anti‐HER2 therapy. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
A behavioral economics‐based telehealth intervention to improve aspirin adherence following hospitalization for acute coronary syndrome
Authors: Riegel Barbara , Stephens‐Shields Alisa , Jaskowiak‐Barr Anne , Daus Marguerite , Kimmel Stephen E. 
Published: April 2020

AbstractPurposeA significant number of patients with acute coronary syndrome (ACS) are nonadherent to aspirin after hospital discharge, with an associated increased risk of subsequent cardiovascular events. The purpose of this pilot study was to test the efficacy of a telehealth intervention based on behavioral economics to improve aspirin adherence following hospitalization for ACS.MethodsWe enrolled 130 participants (c¯X = 58 ± 10.7 years of age, 38% female, 45% black) from two hospitals. Patients were eligible if they owned a smartphone and were admitted to the hospital for ACS, prescribed aspirin at discharge, and responsible for administering their own medications. Consenting participants were randomized to the intervention or usual care group. The intervention group was eligible to receive up to $50 per month if they took their medicine daily, with $2 per day deducted if a dose was missed. All participants received an electronic monitoring (EM) pill bottle containing a 90‐day supply of aspirin, which was used to measure adherence calculated as the proportion of prescribed drug taken using the EM device. Based on the skewness in the adherence distribution, quantile regression was used to evaluate the effect of the intervention on median adherence over time.ResultsAfter 90 days, adherence fell in the control group but remained high in the intervention group (median adherence 81% vs 90%, P = .18). Rehospitalization was higher in the control group (24% vs 13%, P = .17).ConclusionA loss aversion behavioral economics‐based telehealth intervention is a promising approach to improving aspirin adherence following hospitalization for ACS.
Phase‐selective micro‐structural effects on rheological‐networks, segmental relaxation, and electrical conductivity behavior of melt‐mixed polyamide‐12/polypropylene‐multi walled carbon nanotubes ternary nanocomposites
Authors: Sethy Sucharita , Samantara Laxmi , Satapathy Bhabani K. 
Published: April 2020

AbstractMorphological interpretations and their correlation with biphasic rheological networks and subsequent segmental relaxation, and electrical conductivity were comprehensively addressed for polyamide‐12/polypropylene‐multi‐walled carbon nanotubes (PA‐12/PP/MWNT) based ternary nanocomposites fabricated by melt mixing route. The partial migration of MWNT from PP to PA‐12 phase is evident from the spreading coefficient estimations based on interfacial dynamics and transmission electron microscopy (TEM) analysis. Melt rheology measurements based on scaling parameters associated with various viscosity models such as, Cross model, Carreau‐Yasuda model, and Berzin model indicated systematic variation in network rigidity that is in tune with dispersion‐selective nano‐morphology of the nanocomposites. The phase inversion was attained for composition in the range of 50 to 60 wt% of PP‐MWNT content as indicated by Han plot and van‐Gurp Palmen plots which is in direct correspondence to dispersed‐phase‐volume‐fraction range of ~0.3‐0.36. Broadening of loss‐peaks vis‐a‐vis enhanced storage moduli in dynamic mechanical analysis (DMA) signifies the reduced mobility (of polyamide chains) and hence the enhanced stiffness. The electrical conductivity of the nanocomposites post‐annealing decreased at temperatures above 100°C demonstrating the temperature‐sensitive morphology disruption (of the conductive PP‐MWNT channels) in the nanocomposites.
Enhanced foamability of isotactic polypropylene/polypropylene‐grafted‐nanosilica nanocomposites in supercritical carbon dioxide
Authors: Yuan Wenjing , Wang Feng , Gao Chong , Liu Peng , Ding Yanfen , Zhang Shimin , Yang Mingshu 
Published: April 2020

AbstractPolypropylene‐grafted nanosilica (PP‐g‐SiO2) was prepared by us as a new modified nanosilica with long polymer chains and high grafting density. It was found that the addition of PP‐g‐SiO2 resulted in remarkable strain‐hardening behavior of PP. Herein, the foaming behavior of isotactic polypropylene (iPP)/PP‐g‐SiO2 nanocomposites was investigated by using supercritical carbon dioxide (scCO2) as a blowing agent. The results demonstrated that the incorporation of PP‐g‐SiO2 could obviously enhance the foamability of iPP. In particular, the uniform cell distribution and smaller cell size could be obtained by 1 wt% particle loading, and 5 wt% particle content showed a wider foaming temperature range and higher cell density. The noticeable enhancement in the foamability of iPP was attributed to the reinforced melt strength, high melt elasticity and the increased heterogeneous nucleation caused by well dispersed and long polypropylene chains grafted SiO2. These findings provide new insights to improve the foaming ability of iPP with incorporation of modified nanoparticles.
Facilitators and barriers to African American high school students' self‐determination skill expression
Authors: Parker Janise S. , Amabile Avery , Oliver Emily , Garnes Jasmine , Sarathy Ashwini 
Published: April 2020

AbstractWe conducted four focus group interviews with 24 high school youth to examine facilitators and barriers to African American high school students' expression of various self‐determination skills (e.g., choice/decision making, self‐advocacy, goal setting, and attainment etc.). The majority of our research participants were African American, with one student identifying as multiracial (African American and White). Key findings revealed that personal (e.g., desire to graduate from school) and contextual factors (e.g., school counselor and teacher support) influenced the participants' expression of multiple self‐determination skills. We also found that some of the participants' motives for utilizing or not utilizing specific skills were influenced by what they perceived as racist, punitive, and restrictive school practices (e.g., teachers holding negative perceptions about African American students and school counselors restricting their access to advanced courses). Findings from this study support ongoing calls for educators to consider students' cultural backgrounds and lived experiences when promoting their expression of self‐determination skills.
Quantifying large‐scale ecosystem stability with remote sensing data
Authors: White Hannah J. , Gaul Willson , Sadykova Dinara , León‐Sánchez Lupe , Caplat Paul , Emmerson Mark C. , Yearsley Jon M. 
Published: April 2020

AbstractTo fully understand ecosystem functioning under global change, we need to be able to measure the stability of ecosystem functioning at multiple spatial scales. Although a number of stability components have been established at small spatial scales, there has been little progress in scaling these measures up to the landscape. Remote sensing data holds huge potential for studying processes at landscape scales but requires quantitative measures that are comparable from experimental field data to satellite remote sensing. Here we present a methodology to extract four components of ecosystem functioning stability from satellite‐derived time series of Enhanced Vegetation Index (EVI) data. The four stability components are as follows: variability, resistance, recovery time and recovery rate in ecosystem functioning. We apply our method to the island of Ireland to demonstrate the use of remotely sensed data to identify large disturbance events in productivity. Our method uses stability measures that have been established at the field‐plot scale to quantify the stability of ecosystem functioning. This makes our method consistent with previous small‐scale stability research, whilst dealing with the unique challenges of using remotely sensed data including noise. We encourage the use of remotely‐sensed data in assessing the stability of ecosystems at a scale that is relevant to conservation and management practices.
Electronic Modulation of Nickel Disulfide toward Efficient Water Electrolysis
Authors: Dinh Khang Ngoc , Sun Yongxiu , Pei Zengxia , Yuan Ziwen , Suwardi Ady , Huang Qianwei , Liao Xiaozhou , Wang Zhiguo , Chen Yuan , Yan Qingyu 
Published: April 2020

AbstractDeveloping highly efficient earth‐abundant nickel‐based compounds is an important step to realize hydrogen generation from water. Herein, the electronic modulation of the semiconducting NiS2 by cation doping for advanced water electrolysis is reported. Both theoretical calculations and temperature‐dependent resistivity measurements indicate the semiconductor‐to‐conductor transition of NiS2 after Cu incorporation. Further calculations also suggest the advantages of Cu dopant to cathodic water electrolysis by bringing Gibbs free energy of H adsorption at both Ni sites and S sites much closer to zero. It is noteworthy that water dissociation on Cu‐doped NiS2 (Cu‐NiS2) surface is even more favorable than those on NiS2 and Pt(111). Thus, the prepared Cu‐NiS2 shows noticeably improved performance toward alkaline hydrogen and oxygen evolution reactions (HER and OER). Specifically, it requires merely 232 mV OER overpotential to drive 10 mA cm−2; in parallel with Tafel slopes of 46 mV dec−1. Regarding HER, an onset overpotential of only 68 mV is achieved. When integrated as both electrodes for water electrolysis, Cu‐NiS2 needs only 1.64 V to drive 10 mA cm−2, surpassing the state‐of‐the‐art Ir/C–Pt/C couple (1.71 V). This work opens up an avenue to engineer low‐cost and earth‐abundant catalysts performing on par with the noble‐metal‐based one for water splitting.