bluuebunny/crossref_metadata_2025_split huggingface dataset:
The best equilibrium in organizational flexibility-stability continuums
Authors: Laser Jan 
Published: May 2020

Purpose
This work aims to analyse the flexibility-stability continuum and explore the question of where the best equilibrium lies on this continuum and to what extent it can be realized.

Design/methodology/approach
After analysing the concepts of flexibility and stability, along with their trade-off relationship, from a theoretical standpoint, the optimum in the flexibility-stability continuum is determined by means of a triangulation of theories. The subsequent operation to determine best possible practice is also accomplished via a theoretical analysis.

Findings
Organizational flexibility and stability are two poles of a continuum that are interdependent. The optimum in a flexibility-stability continuum lies, according to Gossen's first law, where marginal utility is zero. Determination of the optimum requires a great deal of information, however, which is difficult to collate and process because of its complexity. As an alternative to the “optimum”, “best possible practice” is introduced. This provides an alternative to the less satisfactory method of “best practice according to benchmarking.”

Originality/value
The value of this work lies in finding an optimum in the flexibility-stability continuum. As the (theoretical) optimum is difficult to determine and realize due to inherent complexities, “best possible practice” is presented as an alternative. This takes into account the idea of optimization meaning no improvement is possible if the goal is achieved. “Best possible practice” defines an implementable, best possible state that can be used for organizational goal formulation. To achieve the best possible equilibrium in the flexibility-stability continuum, the respective advantages of stability and flexibility should be ideally exploited to lead to competitive advantage.
Explaining stock market returns in Sub-Saharan Africa using an alternate uncovered interest rate parity framework
Authors: Bondzie Afful Kofi , Opoku William 
Published: May 2020

PurposeSub-Saharan African (SSA) stock exchanges are imperfect and inefficient. Therefore, orthodox finance theories are unable to completely explain their market returns. Such models mainly identify anomalies when applied to the sub-region. Consequently, this paper develops an original theoretical model to better explain market returns on the sub-continent.Design/methodology/approachThis paper develops an alternate analytical framework that combines adaptive expectations, Keynesian LM model and modified uncovered interest parity (UIP) formulations to address empirical anomalies identified by previous literature when analyzing SSA's inefficient stock markets. Using panel data, the study first computes the fixed as well as random effects regressions and, later, a Generalized Method of Moments (GMM) dynamic panel regression for further empirical analysis.FindingsBoth the fixed and random effects regression results indicate that the relative output-money supply disparity and foreign inflation-money supply growth rate spread have positive effects on market returns in SSA. On the other hand, foreign interest rates have an inverse effect. Although the GMM dynamic panel regression has similar results, it additionally finds that market returns in SSA are autoregressive. This suggests that past returns are persistent.Research limitations/implicationsA key implication is that multipliers and transmission mechanisms in SSA may take longer to adjust, thereby limiting short-run market returns. Also, policymakers must encourage a critical mass of firms to list in order to enhance efficiency. Additionally, policy variables significantly influence returns. One limitation is the high market segmentation in SSA. This heightens heterogeneity, emphasizing fixed effects.Practical implicationsAlso, the findings of this study may not apply to all emerging economies as SSA economies are highly heterogeneous.Social implicationsThe segmented nature of SSA stock markets may have implications for income inequality and the distribution of resources within the economy. Also, it indicates that there are limits to how firms use capital markets on the sub-continent.Originality/valueThis paper abstracts from the strict ideal market conditions prescribed by modern finance theories and develops an original modified UIP model. It finds that SSA stock markets may be more sensitive to policy variables, instead of determinants postulated by orthodox finance concepts. The study offers opportunities for further critical examination of returns in imperfect frontier markets.
Reliability analysis of a steam boiler system by expert judgment method and best-fit failure model method: a new approach
Authors: Patil Suyog Subhash , Bewoor Anand K. 
Published: May 2020

PurposeIndia's textile industries play a vital role in the Indian economy. These industries consume the highest thermal energy (steam power). The demand of the steam in process industries is increasing rapidly, and this demand can be met by increasing the capacity utilization of steam boilers. The purpose of this paper is to present a new approach for reliability analysis by expert judgment method.Design/methodology/approachA lack of adequate life data is one of the biggest challenge in the reliability analysis of mechanical systems. This research provides an expert judgment approach for assessing the boiler's reliability characteristics. For this purpose, opinions of experts on time to failure and time to repair data were elicited in the form of statistical distributions. In this work, reliability analysis of the boiler system is carried out by expert judgment method and by using best-fit failure model. The system reliability along with preventive maintenance intervals of all components is also evaluated.FindingsIt is observed that the reliability analysis results obtained by expert judgment method and best-fit failure model method indicate that there are no significant differences. Therefore, in case when insufficient data are available, the expert judgment method can be effectively used. The analysis shows that the feedwater tank, feedwater pump, supply water temperature sensor, strainer, return water temperature sensor, condensate filter, mechanical dust collector, coal crusher and fusible plug are identified as critical components from a reliability perspective, and preventive maintenance strategy is suggested for these components.Originality/valueIn this research paper, a system reliability model by the expert judgment method is developed, and it can be effectively used where insufficient failure data are available. This paper is useful for the comparative evaluation of reliability characteristics of a boiler system by expert judgment method and best-fit failure model method.
Field data for satellite validation and forest structure modeling in a pure and sparse forest of Picea glehnii in northern Hokkaido
Authors: Akitsu Tomoko K. , Nakaji Tatsuro , Yoshida Toshiya , Sakai Rei , Mamiya Wataru , Terigele  , Takagi Kentaro , Honda Yoshiaki , Kajiwara Koji , Nasahara Kenlo N. 
Published: May 2020

AbstractTo validate and to improve ecological products obtained from satellites, such as a leaf area index (LAI), above‐ground biomass (AGB), and a fraction of photosynthetically active radiation (fAPAR), in‐situ accurate data are indispensable. They must be not a single point‐data but an areal data representing the satellite footprint. Their accuracy needs to be much higher than the required accuracy for the satellite products. The quantitative assessment of their error is necessary for evaluating the satellite products' error from the discrepancy between the satellite products and the in‐situ data. However, such data had not been available. In particular, there had been few data of LAI in a sparse evergreen needle‐leaved forest, because of difficulty of accuracy control of in‐situ observation in such a forest. To overcome the difficulty and to obtain the representative LAI, we made an allometric equation to estimate the leaf mass of Picea glehnii in northern Hokkaido. We report the allometric equations of leaf mass and AGB of P. glehnii, its leaf mass per area (LMA), its leaf life span, its leaf distribution, its crown shapes, its wood specific gravity, and tree locations. We also report LAI, AGB, and fAPAR within the 500 m × 500 m area, which is the footprint scale of the Global Change Observation Mission‐Climate satellite, in a pure and sparse forest of P. glehnii in northern Hokkaido. These precise data are useful for validation of other satellite data, especially with higher spatial resolution, and forest structure modeling.The complete data set for this abstract published in the Data Paper section of the journal is available in electronic format in MetaCat in JaLTER at http://db.cger.nies.go.jp/JaLTER/metacat/metacat/ERDP-2020-06.1/jalter-en. [Correction added on 7 September 2020, after first online publication: JaLTER URL has been updated.]
‘Willy nilly’ doctors, bad patients, and resistant bodies in general public explanations of antimicrobial resistance
Authors: Davis Mark D. M. , Lohm Davina B. , Whittaker Andrea , Flowers Paul 
Published: May 2020

AbstractIncreased public engagement is a feature of policy and communications focussed on the reduction of antimicrobial resistance. Explaining antimicrobial resistance for general publics has proven difficult and they continue to endorse apparently mistaken knowledge, including the conflation of antimicrobial resistance with the notion of the resistant body. We interviewed members of the general public in Melbourne, Australia, to explore explanatory models for antimicrobial resistance and shed light on the persistence of the resistant body assumption and related concepts. In the face of AMR’s complexity and the portended antibiotic apocalypse, publics rely on a heavily inscribed understanding of the body defending itself against microbes. Publics also read antibiotic misuse and overuse messages as the responsibility of other patients and medical practitioners, and not themselves. Significantly, the scientific world view that has created expert knowledge about AMR hails publics in ways that discredits them and limits their capacity to take action. Increased engagement with publics will be required to ensure that collaborative and sustainable AMR approaches are fashioned for the future.
Analysis on physicochemical and sensory qualities of soymilk prepared by various cultivars: Application of fuzzy logic technique
Authors: Jin Xuehua , Chen Chen , Guo Shuntang , Zhang Hui 
Published: May 2020

AbstractSoymilk has a complicated system, and its sensory and physicochemical characteristics are influenced by the components of the soybean seeds. Thirty‐five soybean cultivars were selected, and correlation analysis and clustering analysis were applied to determine the significant correlations between soybean seed traits and soymilk physiochemical properties. Four sensory quality attributes of soymilk, including taste, odor, appearance, and mouthfeel, were quantified in numerical values and scored based on a weighting criterion which was constructed via the fuzzy logic technique. Soymilk prepared from the soybean seeds with the lower crude protein and the higher crude fat content displayed better sensory qualities. A multivariate linear regression analysis was used to establish a predictive model for overall sensory scores of soymilk, which could be the reference for soybean cultivars selection in soymilk processing. To comprehensively optimize the processing costs, nutritional values, and sensory qualities, a set of detailed attributes of soybean seeds were recommended based on this study: 100‐seed weight is higher than 20 g; ash content is less than 5.5 g/100 g; crude fat content is 20 to 24 g/100 g; and crude protein content is as high as possible, while the maximum limit is 40 g/100 g.Practical ApplicationThe established predictive model can be a reference for soybean cultivars selection in soymilk processing. Moreover, the soybean composition range that is revealed by this study also provides a recommendation for the soybean breeding.
Fast quantification of short‐chain fatty acids in rat plasma by gas chromatography
Authors: Wang Chung‐Yi , Chen Yu‐Wei , Tain You‐Lin , Chang Sam K.C. , Huang Li‐Tung , Hsieh Chang‐Wei , Hou Chih‐Yao 
Published: May 2020

AbstractShort‐chain fatty acids (SCFAs) are the main metabolites of the intestinal flora and play an important role in the interaction between the intestinal flora and host metabolism. Therefore, reliable methods are needed to accurately measure SCFAs concentrations. SCFAs are commonly analyzed by gas chromatography–mass spectrometry (GC‐MS), which requires lengthy sample treatments and a long run time. This study aimed to develop a fast GC method with formic acid pretreatment for SCFAs quantification in the plasma of rat. Baseline chromatographic resolution was achieved for three SCFAs (acetic, propionic, and butyric) within an analysis time of 10.5 min. The method exhibited good recovery for a wide range of concentrations with a low limit of detection for each compound. The relative standard deviations (RSDs) of all targeted compounds showed good intra‐ and interday precision (<10%). We used our method to measure SCFAs levels in plasma samples from rats fed with a high fructose diet (HFD) to test the accuracy of the developed method. It was shown that SCFAs are indeed affected negatively by a HFD (60% fructose). This method was successfully employed to accurately determine SCFAs in the rat plasma with minimum sample preparation. Results showed potential damage of HFD, which produced lower SCFAs.Practical ApplicationIncreasingly, microbiota and gut health research are being conducted by many food scientists to elucidate the relationships among the factors of food components, particularly the nondigestible carbohydrates, food processing conditions, and potential health impact. This research provides a useful, rapid, and accurate method that can save time in the analysis of short‐chain fatty acids, which are commonly analyzed in gut health research.
Association between algal productivity and phycosphere composition in an outdoor Chlorella sorokiniana reactor based on multiple longitudinal analyses
Authors: Steichen Seth A. , Gao Song , Waller Peter , Brown Judith K. 
Published: May 2020

SummaryMicroalgae as a biofuel source are of great interest. Bacterial phycosphere inhabitants of algal cultures are hypothesized to contribute to productivity. In this study, the bacterial composition of the Chlorella sorokiniana phycosphere was determined over several production cycles in different growing seasons by 16S rRNA gene sequencing and identification. The diversity of the phycosphere increased with time during each individual reactor run, based on Faith’s phylogenetic diversity metric versus days post‐inoculation (R = 0.66, P < 0.001). During summer months, Vampirovibrio chlorellavorus, an obligate predatory bacterium, was prevalent. Bacterial sequences assigned to the Rhizobiales, Betaproteobacteriales and Chitinophagales were positively associated with algal biomass productivity. Applications of the general biocide, benzalkonium chloride, to a subset of experiments intended to abate V. chlorellavorus appeared to temporarily suppress phycosphere bacterial growth, however, there was no relationship between those bacterial taxa suppressed by benzalkonium chloride and their association with algal productivity, based on multinomial model correlations. Algal health was approximated using a model‐based metric, or the ‘Health Index’ that indicated a robust, positive relationship between C. sorokiniana fitness and presence of members belonging to the Burholderiaceae and Allorhizobium–Neorhizobium–Pararhizobium–Rhizobium clade. Bacterial community composition was linked to the efficiency of microalgal biomass production and algal health.
Multilevel approach to male fertility by machine learning highlights a hidden link between haematological and spermatogenetic cells
Authors: Santi Daniele , Spaggiari Giorgia , Casonati Andrea , Casarini Livio , Grassi Roberto , Vecchi Barbara , Roli Laura , De Santis Maria Cristina , Orlando Giovanna , Gravotta Enrica , Baraldi Enrica , Setti Monica , Trenti Tommaso , Simoni Manuela 
Published: May 2020

AbstractBackgroundMale infertility represents a complex clinical condition requiring an accurate multilevel assessment, in which machine learning technology, combining large data series in non‐linear and highly interactive ways, could be innovatively applied.MethodsA longitudinal, observational, retrospective, big data study was carried out, applying for the first time the ML in the context of male infertility. A large database including all semen samples collected between 2010 and 2016 was generated, together with blood biochemical examinations, environmental temperature and air pollutants exposure. First, the database was analysed with principal component analysis and multivariable linear regression analyses. Second, classification analyses were performed, in which patients were a priori classified according to semen parameters. Third, machine learning algorithms were applied in a training phase (80% of the entire database) and in a tuning phase (20% of the data set). Finally, conventional statistical analyses were applied considering semen parameters and those other variables extracted during machine learning.ResultsThe final database included 4239 patients, aggregating semen analyses, blood and environmental parameters. Classification analyses were able to recognize oligozoospermic, teratozoospermic, asthenozoospermic and patients with altered semen parameters (0.58 accuracy, 0.58 sensitivity and 0.57 specificity). Machine learning algorithms detected three haematological variables, that is lymphocytes number, erythrocyte distribution and mean globular volume, significantly related to semen parameters (0.69 accuracy, 0.78 sensitivity and 0.41 specificity).ConclusionThis is the first machine learning application to male fertility, detecting potential mathematical algorithms able to describe patients' semen characteristics changes. In this setting, a possible hidden link between testicular and haematopoietic tissues was suggested, according to their similar proliferative properties.
Pension Funding Regulations and Actuarial Gains and Losses
Authors: Heo Kyongsun , Pae Jinhan 
Published: May 2020

AbstractWith pervasive pension funding deficits, Korean firms have been under pressure to improve their funding levels. We examine whether firms have incentives to set obligation‐decreasing pension assumptions when they have large pension deficits (pension obligations in excess of plan assets) and when they make insufficient contributions to external pension funds. We find that firms report larger actuarial gains (or smaller actuarial losses) associated with the remeasurement of pension liabilities when their pension funding ratio (the ratio of the fair value of plan assets to defined benefit obligations) is lower and when contributions to plan assets relative to pension service costs are smaller. Next, upon the introduction of a minimum pension funding guideline, we find that the effect of the funding ratio and contributions to pension funds on actuarial gains and losses is more pronounced for firms whose funding ratios are slightly below the minimum funding ratio than it is for firms whose funding ratios exceed or fall short of the minimum by a large margin. Our results indicate that firms opportunistically exercise discretion regarding corporate pension accounting under International Financial Reporting Standards to comply with pension funding regulations, thereby reducing perceived pension deficits.
Multimodal learning analytics to investigate cognitive load during online problem solving
Authors: Larmuseau Charlotte , Cornelis Jan , Lancieri Luigi , Desmet Piet , Depaepe Fien 
Published: May 2020

AbstractTo have insight into cognitive load (CL) during online complex problem solving, this study aimed at measuring CL through physiological data. This study experimentally manipulated intrinsic and extraneous load of exercises in the domain of statistics, resulting in four conditions: high complex with hints, low complex with hints, high complex without hints and low complex without hints. The study had a within‐subject‐design in which 67 students solved the exercises in a randomized order. Self‐reported CL was combined with physiological data, namely, galvanic skin response (GSR), skin temperature (ST), heart rate (HR) and heart rate variability (HRV). Multiple imputation was used for handling missing data from resp. 16 and 19 students for GSR/ST and HR/HRV. First, differences between conditions in view of physiological data were examined. Second, we investigated how much variance of self‐reported CL and task performance was explained by physiological data. Finally, we investigated which features can be used to assess (objective) CL. Results revealed no significant differences between the manipulated conditions in terms of physiological data. Nonetheless, HR and ST were significantly related to self‐reported CL, whereas ST to task performance. Additionally, this study revealed the potential of ST and HR to assess high CL.
Hepatic C9 cells switch their behaviour in short or long exposure to soft substrates
Authors: Cabriales Lucia , Hautefeuille Mathieu , Vázquez‐Victorio Genaro , Martinez‐Pastor David , Carretero‐Ortega Jorge , Jiménez‐Escobar Alejandra , Macias‐Silva Marina 
Published: May 2020

Background InformationThere have been several studies to understand the influence of stiffness of the culture substrates for different types of adherent cells. It is generally accepted that cell proliferation, spreading and focal adhesions increase with higher matrix stiffness. However, what remains unclear is whether this kind of cell behaviour may be reverted by culturing on soft substrates those cell lines that were originally selected or primed on stiff surfaces.ResultsHere, we studied the influence of substrate softness on proliferation, adhesion and morphology of the highly proliferative hepatic C9 cell line. We cultured C9 cells on soft and stiff polydimethylsiloxane (PDMS) substrates prepared with two different elastic moduli in the range of 10 and 200 kPa, respectively. Lower cell proliferation was observed on substrates with lower stiffness without affecting cell viability. The proliferation rate of C9 cell line along with extracellular growth‐regulated kinase (ERK) phosphorylation was decreased on soft PDMS. Despite this cell line has been described as a hepatic epithelial cell, our characterisation demonstrated that the origin of C9 cells is uncertain, although clearly epithelial, with the expression of markers of several hepatic cells. Surprisingly, consecutive passages of C9 cells on soft PDMS did not alter this mesenchymal phenotype, vimentin expression did not decrease when culturing cells in soft substrates, even though the ERK phosphorylation levels eventually were increased after several passages on soft PDMS, triggering again an increase of cell proliferation.Conclusions and SignificanceThis study shows that the exposure of C9 cells to soft substrates promoted a decrease of cell proliferation rate, as reported for other types of cells on PDMS, whereas a much longer term exposure caused cells to adapt to softness after trained for several passages, reactivating proliferation. During this phenomenon, the morphology and phenotype of trained cells was modified accompanying the increase of cell proliferation rate contrary to the effect observed in short periods of cell culture. In contrast to previous reports, cell death was not observed during these experiments, discarding a cell selection mechanism and suggesting soft cell adaptation may be limited in time in C9 cells.