bluuebunny/crossref_metadata_2025_split huggingface dataset:
Antecedents and consequences of collective psychological ownership: The validation of a conceptual model
Authors: Giordano Ana Paula , Patient David , Passos Ana Margarida , Sguera Francesco 
Published: November 2019

SummaryWe investigate team member feelings of collective psychological ownership (CPO) over teamwork products, the psychological paths that lead to it, and its impact on team workers' evaluations of team effectiveness, turnover intentions, and intentions to champion teamwork products. We focus on the teamwork product as an important target of ownership feelings, building on theories of self‐extension, psychological ownership, and team emergent states. In Study 1, we validate measures for three ownership activating experiences (OAE) that have been proposed as paths to CPO (control over, intimate knowledge regarding, and investment in the teamwork product) using two samples of individual team workers (n = 210 and n = 140). In Study 2 (n = 183) and Study 3 (n = 200), we use surveys and a multiwave design to show that team workers' feelings of CPO mediate the relationship between investment in and intimate knowledge regarding the product and team effectiveness evaluations, team turnover intentions, and intentions to champion the work product. In Study 4 (n = 48 teams), CPO was predicted by the ownership activating experiences, at the team level. This research additionally highlights the benefits to organizations of creating conditions for the emergence of employee feelings of shared ownership over teamwork products.
Subjective time in organizations: Conceptual clarification, integration, and implications for future research
Authors: Tang Shi , Richter Andreas W. , Nadkarni Sucheta 
Published: November 2019

SummaryDespite the rapid growth of organizational research on subjective time, the extant literature is fragmented due to a lack of conceptual clarification and integration of temporal constructs. To address this fragmentation, we synthesize temporal research from both organizational behavior and adjacent disciplines (i.e., strategy, entrepreneurship, and organizational theory) and introduce a framework that allocates temporal constructs according to their basic conceptual nature (trait–state) and level of analysis (individual–collective). We employed the Linguistic Inquiry and Word Count text analysis to determine the trait–state property of the constructs and a coding method to determine their level of analysis. This framework categorizes four generic types of subjective time: individual temporal disposition, individual temporal state, collective temporal state, and collective temporal disposition. We clarify the conceptualizations of the temporal constructs belonging to each of the four archetypes of subjective time and review their key findings in the organizational literature. Based on this integrative framework, we identify critical knowledge gaps in the current state of research and chart a future agenda with specific suggestions.
Modelling the vegetation response to the 8.2 ka bp cooling event in Europe and Northern Africa
Authors: Li Huan , Renssen Hans , Roche Didier M. , Miller Paul A. 
Published: November 2019

ABSTRACTThe 8.2 ka bp cooling event is assumed to be the most clearly marked abrupt climate event in the Holocene at northern mid‐ to high latitudes. In this study, we simulate the vegetation responses to the 8.2 ka bp climate change event over Europe and Northern Africa. Our results show that all dominant plant functional types (PFTs) over Europe and North Africa respond to these climate changes, but the magnitude, timing and impact factor of their responses are different. Compared with pollen‐based vegetation reconstructions, our simulation generally captures the main features of vegetation responses to the 8.2 ka bp event. Interestingly, in Western Europe, the simulated vegetation after perturbation is different from its initial state, which is consistent with two high‐resolution pollen records. This different vegetation composition indicates the long‐lasting impact of abrupt climate change on vegetation through eco‐physiological and ecosystem demographic processes, such as plant competition. Moreover, our simulations suggest a latitudinal gradient in the magnitude of the event, with more pronounced vegetation responses to the severe cooling in the north and weaker responses to less severe cooling in the south. This effect is not seen in pollen records. © 2019 The Authors. Journal of Quaternary Science Published by John Wiley & Sons, Ltd.
A review of the applications of Raman spectroscopy for breast cancer tissue diagnostic and their histopathological classification of epithelial to mesenchymal transition
Authors: Sabtu Siti Norbaini , Abdul Sani S.F. , Bradley D.A. , Looi L.M. , Osman Z. 
Published: November 2019

AbstractBreast cancer is one of the leading cancers in women worldwide. Notwithstanding the clear advances being made in treatment, early diagnosis of the disease can certainly be expected to reduce morbidity and mortality. With increasing evidence of the role of epithelial to mesenchymal transition (EMT) in tumour progression, early detection of this phenomenon is suggested to be important given that the majority of breast cancer deaths are due to tumour invasion and metastasis. Although histopathology and biomedical imaging techniques continue to be used as standard procedures in breast cancer diagnosis, these techniques have a number of disadvantages, including being time‐consuming, the imaging in particular having attendant limited resolution, sensitivity, and specificity, leading to results that are prone to errors in human interpretation. Due to its rapidity and high specificity, Raman spectroscopy has emerged as a diagnostic tool for breast cancer, useful in identifying malignancy of breast cells, correlated with the EMT phenotype, expressed at the molecular level. Detailed biochemical information from tissue biopsies can also be provided from use of this technique. The use of Raman spectroscopy in breast cancer investigations over the past 10 years and more, including in the study of EMT, is reviewed in the present work also listing the corresponding Raman peaks reported in the literature in seeking to better facilitate identification of peaks of interest.
Experimental investigations on the regeneration of desulfurized 1‐butyl‐3‐methylimidazolium tetrachloroferrate [Bmim][FeCl4] and 1‐butyl‐3‐methylimidazolium thiocyanate [Bmim][SCN] ionic liquids: A raman spectroscopic study
Authors: Ullah Sami , Bustam Mohamad Azmi , Al‐Sehemi Abdullah G. , Assiri Mohammed Ali , Gonfa Girma , Mukhtar Ahmad , Ayoub Muhammad , Ahmad Tausif 
Published: November 2019

AbstractThe room temperature and task‐specific ionic liquids nowadays have been investigated widely for the removal of sulfur compounds from the natural gas streams. However, the major challenge is the recovery of the desulfurized ionic liquids, which need some significant developments. In this study, two magnetic ionic liquids including the 1‐butyl‐3‐methylimidazolium tetrachloroferrate [Bmim][FeCl4] and 1‐butyl‐3‐methylimidazolium thiocyanate [Bmim][SCN] were investigated for their interaction with the sulfur‐rich compound, that is, dibenzothiophene. The ionic liquids samples were desulfurized and then regenerated with the co‐solvent hexane. The samples were characterized and investigated with the analytical techniques including the Fourier‐transform infrared spectroscopy, ultraviolet–visible absorption analysis, thermogravimetric analysis, and detailed analysis by Raman spectroscopy. The desulfurization results demonstrated that there is no significant influence of the dibenzothiophene molecules on the basic structures of ionic liquids. The regeneration results revealed that the high polarity of the co‐solvent hexane successfully dissolve the dibenzothiophene and efficiently separated from the ionic liquids. Hence, the work present here in this study could be applied for the extractive removal of sulfur compounds from ionic liquids for their regeneration using high polarity co‐solvent hexane.
Joint synthesis of conditionally related multiple outcomes makes better use of data than separate meta‐analyses
Authors: Anwer Sumayya , Ades A.E. , Dias Sofia 
Published: November 2019

BackgroundWhen there are structural relationships between outcomes reported in different trials, separate analyses of each outcome do not provide a single coherent analysis, which is required for decision‐making. For example, trials of intrapartum anti‐bacterial prophylaxis (IAP) to prevent early onset group B streptococcal (EOGBS) disease can report three treatment effects: the effect on bacterial colonisation of the newborn, the effect on EOGBS, and the effect on EOGBS conditional on newborn colonisation. These outcomes are conditionally related, or nested, in a multi‐state model.This paper shows how to exploit these structural relationships, providing a single coherent synthesis of all the available data, while checking to ensure that different sources of evidence are consistent.ResultsOverall, the use of IAP reduces the risk of EOGBS (RR: 0.03; 95% Credible Interval (CrI): 0.002–0.13). Most of the treatment effect is due to the prevention of colonisation in newborns of colonised mothers (RR: 0.08, 95% CrI: 0.04–0.14). Node‐splitting demonstrated that the treatment effect calculated using only direct evidence was consistent with that predicted from the remaining evidence (p = 0.15). The findings accorded with previously published separate meta‐analyses of the different outcomes, once these are re‐analysed correctly accounting for zero cells.ConclusionMultiple outcomes should be synthesised together where possible, taking account of their structural relationships. This generates an internally coherent analysis, suitable for decision making, in which estimates of each of the treatment effects are based on all available evidence (direct and indirect). Separate meta‐analyses of each outcome have none of these properties.
Cumulative risk assessment of phthalates in edible vegetable oil consumed by Chinese residents
Authors: Xiang Wei , Gong Qin , Xu Jian , Li Kailong , Yu Fengxiang , Chen Ting , Qin Si , Li Can , Wang Fangbin 
Published: November 2019

AbstractBACKGROUNDPhthalates have been widely used as plasticizers in various industries and are widely focused on in the international community as a result of their reproductive toxicity. Exposure of Chinese residents to phthalates via edible vegetable oil occurs often. In the present study, gas chromatography–mass spectrometry was used to detect the two main phthalates bis(2‐ethylhexyl) phthalate (DEHP) and dibutyl phthalate (DBP) in four major edible vegetable oil sources: an edible oil blend, soybean oil, peanut oil and rapeseed oil (a total of 1016 samples), as collected throughout China. Furthermore, cumulative risk assessment was used to estimate the reproductive health risk to Chinese residents caused by the phthalates that come from edible vegetable oils.RESULTSBoth phthalates were detected in four major edible vegetable oil sources. The phthalate with the highest detection rate was DBP (13.48%), followed by DEHP (7.78%). The results of the cumulative risk assessment showed that the hazard indices of these two phthalates in edible vegetable oils were less than 1, except in soybean oil. Nevertheless, the two phthalates had the lowest detection rates in soybean oil, which were 1.94% (DEHP) and 5.16% (DBP). In China, contamination levels of phthalates in the soils where oil crops are cultivated have a great influence on the phthalate concentrations in edible vegetable oils.CONCLUSIONIt is recommended that Chinese residents who are consuming soybean oil choose well‐known brands and regularly change their brand of consumption. The phthalates in edible vegetable oils pose a relatively small reproductive health risk to Chinese residents. © 2019 Society of Chemical Industry
Temperature and pH growth profile prediction of newly isolated bacterial strains from alkaline soils
Authors: Šovljanski Olja , Tomić Ana , Pezo Lato , Markov Siniša 
Published: November 2019

AbstractBACKGROUNDSoil microorganisms can form complex and varied communities which interact with each other in many different ways depending on environmental conditions. These microbial diversities are accompanied by different metabolic paths and adaptability reflected even in extreme environments. In recent decades, the biodiversity of microbes in extreme environments has been in scientific focus because such specifically adapted bacteria can improve bioremediation processes in industrial and agricultural applications. Instead of the time‐consuming process of identification of new bacterial strains from habitats rich in microbiota, artificial neural networks have been proposed as a mapping model for resolving the problem of prediction of microbial behaviour.RESULTSThe occurrence and diversity of alkaliphilic sporogenic bacteria in alkaline soils were investigated. For this purpose, soil samples were collected from various locations: leached soil from the Danube river, cement factory wastewater accumulation, deposit of limestone near the Bešenovo lake and the Beli Majdan cave in the Fruška gora mountain. According to the obtained results, two empirical models were developed that gave a good fit to experimental data and were able to predict successfully the pH and temperature growth profiles of the natural isolates. The artificial neural network models showed a reasonably good predictive capability (overall R2 for temperature growth profile was 0.727, while the overall R2 for pH growth profile was 0.906).CONCLUSIONSThe developed mathematical models provided adequate precision for practical study in the microbiology laboratory and scale‐up processes for a wide range of laboratory and industrial applications, where specifically adapted microbial communities are needed. © 2019 Society of Chemical Industry
Aqueous extract from leaves of Ludwigia hyssopifolia (G. Don) Exell as potential bioherbicide
Authors: Mangao Arnoldus M , Arreola Sheryl Lozel B , San Gabriel Elgin V , Salamanez Kevin C 
Published: November 2019

AbstractBACKGROUNDLudwigia hyssopifolia (G. Don) Exell, one of the problem weeds in some rice‐producing countries, was studied to determine its allelopathic potential based on the effects of aqueous extracts of its tissues (leaves, roots and stem) on seedling growth of selected weeds and rice. The major phenolic compound of its leaves was also isolated and characterized.RESULTSL. hyssopifolia aqueous leaf extract showed significant inhibition of shoot growth and biomass accumulation of weeds (Amaranthus spinosus L., Dactyloctenium aegyptium L., Cyperus iria L.) while maintaining less adverse effects on rice (crop) compared to other aqueous extracts of roots and stem. Phytochemical screening showed that phenols, tannins, flavonoids, terpenoids, saponins and coumarins are found in its leaf aqueous extract. The Folin–Ciocalteu method revealed that its leaves contain 26.66 ± 0.30 mg GAE g−1 leaf. The extract was then acid‐hydrolyzed to liberate the phenolics (25 mg phenolics g−1 leaf). The major compound was isolated via preparative thin‐layer chromatography using formic acid–ethyl acetate–n‐hexane (0.05:4:6) solvent system. It had maximum UV absorption at 272 nm while its Fourier transform infrared spectrum revealed phenol, carboxylic acid and ether functionalities. This also had similar chromatographic mobility when run together with syringic acid in two‐dimensional paper chromatography and thin‐layer chromatography.CONCLUSIONSL. hyssopifolia has potential allelopathic activity and its leaf aqueous extract showed the highest phytotoxic activity (P ≤ 0.05) indicating its potential as a bioherbicide. The most probable identity of the major phenolic compound is syringic acid. © 2019 Society of Chemical Industry
Trace analysis of rimantadine in human urine after dispersive liquid liquid microextraction followed by liquid chromatography–post column derivatization
Authors: Zacharis Constantinos K. , Tzanavaras Paraskevas D. 
Published: November 2019

AbstractThe first dispersive liquid liquid microextraction scheme followed by liquid chromatography‐post column derivatization for the determination of the antiviral drug rimantadine in urine samples is demonstrated. The effect of the type and volume of organic extraction solvent, type and volume of disperser solvent, sample pH, ionic strength, extraction time, and centrifugation speed on the extraction efficiency were studied. Rimantadine and the internal standard (amantadine) were chromatographed using a reversed phase monolithic stationary phase with a mixture of equal volumes of methanol and phosphate buffer (pH = 3) as mobile phase. On‐line post‐column derivatization of the analyte was performed using a “two‐stream” manifold with o‐phthalaldehyde and N‐acetyl‐cysteine at alkaline medium. Under the optimized extraction conditions, the enrichment factor of rimantadine was 58. The linear range was 5–100 µg/L with correlation coefficient r of 0.9984 while the limit of detection achieved was 0.5 µg/L. The within‐day and between‐day precision for the tested concentration levels were less than 14.3% and the mean recoveries obtained from the spiked samples were ranged between 87.5 and 113.9%. The main advantages of the proposed method are the simplicity of operation, rapidity, low cost, and low limit of detection of the analyte.
Spatial pattern and temporal trend of land degradation in the Heihe River Basin of China using local net primary production scaling
Authors: Li Feng , Meng Jijun , Zhu Likai , You Nanshan 
Published: November 2019

AbstractBiophysical processes and people's livelihoods largely depend on ecosystem productivity; thus, land degradation is harmful for local sustainable development. Most previous assessments of land degradation used a comprehensive index system or trend analysis without localized benchmarks; thus, they were not fully objective. Here, we assessed the land degradation in the Heihe River Basin (HRB), China using the local net primary production (NPP) scaling (LNS) method. We improved the method by dividing land capability classes (LCC) using remote sensing data, and determining the reference NPP for each LCC to represent the productivity under optimal environmental conditions. To assess the extent, severity and trend of land degradation, we obtained LNS percent values which was defined as the ratio of present NPP to reference NPP. We categorized our identified land degradation hotspots, determined their causes and proposed potential strategies for land conservation. Our results showed that nearly one quarter of the area was degraded land, mainly located in the upper stream. The average NPP was 35.75% lower than the reference NPP, with a reduction amount of 0.82 GgC yr−1. Only the lower stream showed a significant decreasing trend in LNS percent values. The areas with a positive trend in LNS percent values were primarily observed in the middle stream croplands. We found the degradation condition deteriorated first and recovered later in the HRB. Land use change contributed more than climate change to the local NPP of the degraded areas. Our research provides a more general framework for assessing land productivity reduction induced by anthropogenic and natural processes in the drylands.
Topological Edge States and Gap Solitons in the Nonlinear Dirac Model
Authors: Smirnova Daria A. , Smirnov Lev A. , Leykam Daniel , Kivshar Yuri S. 
Published: November 2019

AbstractTopological photonics has emerged recently as a novel approach for realizing robust optical circuitry, and the study of nonlinear effects in topological photonics is expected to open the door for tunability of photonic structures with topological properties. Here, the topological edge states and topological gap solitons which reside in the same band gaps described by the nonlinear Dirac model are studied, in both one and two dimensions. Strong nonlinear interactions between these dissimilar topological modes, manifested in the efficient excitation of topological edge states by scattered traveling gap solitons are revealed. Nonlinear tunability of localized states is explicated with exact analytical solutions for the two‐component spinor wave function. Our studies are complemented by spatiotemporal numerical modeling of the nonlinear scattering in 1D and 2D photonic lattices.
Local well‐posedness of the Hall‐MHD system in Hs(Rn) with s>n2
Authors: Dai Mimi 
Published: November 2019

AbstractWe establish local well‐posedness of the Hall‐magneto‐hydrodynamics (Hall‐MHD) system in the Sobolev space with , . The previously known local well‐posedness Sobolev space was with . Thus the result presented here is an improvement. Moreover, we show that the solution of the Hall‐MHD system in the space with converges to a solution of the MHD system when the Hall effect coefficient goes to zero.
Antecedents, consequences, and reducers of perceived risk in social media: A systematic literature review and directions for further research
Authors: Rehman Zia Ur , Baharun Rohaizat , Salleh Nor Zafir Md 
Published: November 2019

AbstractThe social media has become an integral part of the marketing strategy. Marketing activities are now more inclined to online social networks (OSNs) than ever before in the history of the business. More and more consumers are joining OSNs for the sake of fun, socialization, and online buying. Every user perceives some degree of risk while joining and using OSNs. The current systematic literature review gathers and synthesizes research records of the last 9 years (2010–18) on consumer perceived risks concerning OSNs. We used PRISMA as a protocol to conduct this systematic literature review. The synthesis provides a detailed account of the perceived risk factors, their antecedents and consequences, risk‐reducing strategies, and future research potential in the said domain.
Inverse‐QSPR for de novo Design: A Review
Authors: Gantzer Philippe , Creton Benoit , Nieto‐Draghi Carlos 
Published: November 2019

AbstractThe use of computer tools to solve chemistry‐related problems has given rise to a large and increasing number of publications these last decades. This new field of science is now well recognized and labelled Chemoinformatics. Among all chemoinformatics techniques, the use of statistical based approaches for property predictions has been the subject of numerous research reflecting both new developments and many cases of applications. The so obtained predictive models relating a property to molecular features – descriptors – are gathered under the acronym QSPR, for Quantitative Structure Property Relationships. Apart from the obvious use of such models to predict property values for new compounds, their use to virtually synthesize new molecules – de novo design – is currently a high‐interest subject. Inverse‐QSPR (i‐QSPR) methods have hence been developed to accelerate the discovery of new materials that meet a set of specifications. In the proposed manuscript, we review existing i‐QSPR methodologies published in the open literature in a way to highlight developments, applications, improvements and limitations of each.