bluuebunny/crossref_metadata_2025 huggingface dataset:
The neurocognitive gains of diagnostic reasoning training using simulated interactive veterinary cases
Authors: Nassar Maaly
Published: May 2019

The present longitudinal study ascertained training-associated transformations in the neural underpinnings of diagnostic reasoning, using a simulation game named “Equine Virtual Farm” (EVF). Twenty participants underwent structural, EVF/task-based and resting-state MRI and diffusion tensor imaging (DTI) before and after completing their training on diagnosing simulated veterinary cases. Comparing playing veterinarian versus seeing a colorful image across training sessions revealed the transition of brain activity from scientific creativity regions pre-training (left middle frontal and temporal gyrus) to insight problem-solving regions post-training (right cerebellum, middle cingulate and medial superior gyrus and left postcentral gyrus). Further, applying linear mixed-effects modelling on graph centrality metrics revealed the central roles of the creative semantic (inferior frontal, middle frontal and angular gyrus and parahippocampus) and reward systems (orbital gyrus, nucleus accumbens and putamen) in driving pre-training diagnostic reasoning; whereas, regions implicated in inductive reasoning (superior temporal and medial postcentral gyrus and parahippocampus) were the main post-training hubs. Lastly, resting-state and DTI analysis revealed post-training effects within the occipitotemporal semantic processing region. Altogether, these results suggest that simulation-based training transforms diagnostic reasoning in novices from regions implicated in creative semantic processing to regions implicated in improvised rule-based problem-solving.
Population Health Genetic Screening for Tier 1 Inherited Diseases in Northern Nevada: 90% of At-Risk Carriers are Missed
Authors: Grzymski JJ , Elhanan G , Smith E , Rowan C , Slotnick N , Dabe S , Schlauch K , Read R , Metcalf WJ , Lipp B , Reed H , Levin E , Kao J , Rashkin M , Bowes J , Bolze A , Dunaway K , Washington N , Slonim A , Lu JT
Published: May 2019

In an unselected population of 23,713 participants who underwent clinical exome sequencing as a part of the Healthy Nevada Project (HNP) in Northern Nevada (Renown Health, Reno, Nevada) from March 15, 2018, to Sept 30, 2018 (Table S1) we find a 1.26% carrier rate for expected pathogenic and likely pathogenic genetic variants in (FH: LDLR, PCSK9, APOB), Hereditary Breast and Ovarian Cancer (HBOC: BRCA1, BRCA2) and Lynch Syndrome (LS: MLH1, MSH2, MSH6, PSM2) with over 90% of carriers undetected under current medical practice. 26% of carriers were found to have advanced disease with 70% first diagnosed before the age of 65. Less than 20% of all carriers had any documented suspicion for inherited genetic disease in the medical record and upon direct follow-up survey under 40% of carriers had family history of relevant disease. A population preventative genetic screening approach for patients under 45 may improve outcomes.
Higher Meta-cognitive Ability Predicts Less Reliance on Over Confident Habitual Learning System
Authors: Ershadmanesh Sara , Miandari Mostafa , Vahabie Abdol-hossein , Ahmadabadi Majid Nili
Published: May 2019

Many studies on human and animals have provided evidence for the contribution of goal-directed and habitual valuation systems in learning and decision-making. These two systems can be modeled using model-based (MB) and model-free (MF) algorithms in Reinforcement Learning (RL) framework. Here, we study the link between the contribution of these two learning systems to behavior and meta-cognitive capabilities. Using computational modeling we showed that in a highly variable environment, where both learning strategies have chance level performances, model-free learning predicts higher confidence in decisions compared to model-based strategy. Our experimental results showed that the subjects’ meta-cognitive ability is negatively correlated with the contribution of model-free system to their behavior while having no correlation with the contribution of model-based system. Over-confidence of the model-free system justifies this counter-intuitive result. This is a new explanation for individual difference in learning style.
Stimulus presentation rates affect performance but not the acquired knowledge – Evidence from procedural learning
Authors: Kiss Mariann , Nemeth Dezso , Janacsek Karolina
Published: May 2019

Presentation rates – the tempo in which we encounter subsequent items – can alter both our behavioral and neural responses in cognitive domains such as learning, memory, decision-making, perception and language. However, it is still unclear to what extent presentation rates affect the momentary performance versus the underlying cognitive function or mental representation. Here we systemically tested the effect of presentation rate on performance versus competence in procedural learning – a fundamental cognitive function that underlies the acquisition of skills and habits. Procedural learning was assessed by a probabilistic sequence learning task, in which learning typically occurs implicitly. Stimulus presentation rates were systematically manipulated by the Response-to-Stimulus-Intervals (RSIs). Participants were assigned to a fast (120ms) RSI or a slow (850ms) RSI group during the Learning phase, and were tested with both RSIs 24 hours later (Testing phase). We also tested whether they gained explicit knowledge about the sequence or their knowledge remained implicit. We found that the slower RSI led to weaker performance in the Learning phase. Importantly, however, the results of the Testing phase showed that this effect was primarily due to the expression of the acquired knowledge and not the learning itself. Thus, the slower presentation rate affected performance rather than competence. The acquired knowledge remained implicit in both groups, regardless of the presentation rate during learning. These findings call for tasks that can dissociate competence from performance both in experimental and clinical settings. Additionally, our findings can help design more efficient training protocols in education and clinical rehabilitation.
A Universal Nonparametric Event Detection Framework for Neuropixels Data
Authors: Chen Hao , Chen Shizhe , Deng Xinyi
Published: May 2019

Neuropixels probes present exciting new opportunities for neuroscience, but such large-scale high-density recordings also introduce unprecedented challenges in data analysis. Neuropixels data usually consist of hundreds or thousands of long stretches of sequential spiking activities that evolve non-stationarily over time and are often governed by complex, unknown dynamics. Extracting meaningful information from the Neuropixels recordings is a non-trial task. Here we introduce a general-purpose, graph-based statistical framework that, without imposing any parametric assumptions, detects points in time at which population spiking activity exhibits simultaneous changes as well as changes that only occur in a subset of the neural population, referred to as “change-points”. The sequence of change-point events can be interpreted as a footprint of neural population activities, which allows us to relate behavior to simultaneously recorded high-dimensional neural activities across multiple brain regions. We demonstrate the effectiveness of our method with an analysis of Neuropixels recordings during spontaneous behavior of an awake mouse in darkness. We observe that change-point dynamics in some brain regions display biologically interesting patterns that hint at functional pathways, as well as temporally-precise coordination with behavioral dynamics. We hypothesize that neural activities underlying spontaneous behavior, though distributed brainwide, show evidences for network modularity. Moreover, we envision the proposed framework to be a useful off-the-shelf analysis tool to the neuroscience community as new electrophysiological recording techniques continue to drive an explosive proliferation in the number and size of data sets.
In-vitro and in-vivo Characterization of a Multi-Stage Enzyme-Responsive Nanoparticle-in-Microgel Pulmonary Drug Delivery System
Authors: Mejías Joscelyn C. , Roy Krishnendu
Published: May 2019

Although the lung is an obvious target for site-specific delivery of many therapeutics for respiratory airway diseases such as asthma, COPD, and cystic fibrosis, novel strategies are needed to avoid key physiologic barriers for efficient delivery and controlled release of therapeutics to the lungs. Specifically, deposition into the deep lung requires particles with a 1-5 µm aerodynamic diameter; however, particles with a geometric diameter less than 6 µm are rapidly cleared by alveolar macrophages. Additionally, epithelial, endothelial, and fibroblast cells prefer smaller (< 300 nm) nanoparticles for efficient endocytosis. Here we address these contradictory design requirements by using a nanoparticle-inside-microgel system (Nano-in-Microgel). Using an improved maleimide-thiol based Michael Addition during (water-in-oil) Emulsion (MADE) method, we fabricated both trypsin-responsive and neutrophil elastase-responsive polymeric Nano-in-Microgel to show the versatility of the system in easily exchanging enzyme-responsive crosslinkers for disease-specific proteases. By varying the initial macromer concentration, from 20-50 % w/v, the size distribution means ranged from 4-8 µm, enzymatic degradation of the microgels is within 30 minutes, and in vitro macrophage phagocytosis is lower for the higher % w/v. We further demonstrated that in vivo lung delivery of the multi-stage carriers through the pulmonary route yields particle retention up to several hours and followed by clearance within in naïve mice. Our results provide a further understanding of how enzymatically-degradable multi-stage polymeric carriers can be used for pulmonary drug delivery.

Graphical Abstract
Population-based neuroimaging reveals traces of childbirth in the maternal brain
Authors: de Lange Ann-Marie G. , kaufmann Tobias , van der Meer Dennis , Maglanoc Luigi , Alnæs Dag , Moberget Torgeir , Douaud Gwenaëlle , Andreassen Ole A. , Westlye Lars T.
Published: May 2019

Pregnancy and childbirth involve maternal brain adaptations that promote attachment to and protection of the newborn. Using brain imaging and machine learning, we provide evidence for a positive relationship between number of childbirths and a ‘younger-looking’ brain in 12,021 women, which could not be explained by common genetic variation. The findings demonstrate that parity can be linked to brain health later in life.
Metric Learning on Expression Data for Gene Function Prediction
Authors: Makrodimitris Stavros , Reinders Marcel J.T. , Ham Roeland C.H.J. van
Published: May 2019

Motivation

Co-expression of two genes across different conditions is indicative of their involvement in the same biological process. However, using RNA-Seq datasets with many experimental conditions from diverse sources introduces batch effects and other artefacts that might obscure the real co-expression signal. Moreover, only a subset of experimental conditions is expected to be relevant for finding genes related to a particular Gene Ontology (GO) term. Therefore, we hypothesize that when the purpose is to find similar functioning genes that the co-expression of genes should not be determined on all samples but only on those samples informative for the GO term of interest.

Results

To address both types of effects, we developed MLC (Metric Learning for Co-expression), a fast algorithm that assigns a GO-term-specific weight to each expression sample. The goal is to obtain a weighted co-expression measure that is more suitable than the unweighted Pearson correlation for applying Guilt-By-Association-based function predictions. More specifically, if two genes are annotated with a given GO term, MLC tries to maximize their weighted co-expression, and, in addition, if one of them is not annotated with that term, the weighted co-expression is minimized. Our experiments on publicly available Arabidopsis thaliana RNA-Seq data demonstrate that MLC outperforms standard Pearson correlation in term-centric performance.

Availability

MLC is available as a Python package at www.github.com/stamakro/MLC

Contact

s.makrodimitris@tudelft.nl

Supplementary information

Supplementary data are available online.
Spectral partitioning identifies individual heterogeneity in the functional network topography of ventral and anterior medial prefrontal cortex
Authors: Toro-Serey Claudio , Tobyne Sean M. , McGuire Joseph T.
Published: May 2019

Regions of human medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC) are part of the default network (DN), and additionally are implicated in diverse cognitive functions ranging from autobiographical memory to subjective valuation. Our ability to interpret the apparent co-localization of task-related effects with DN-regions is constrained by a limited understanding of the individual-level heterogeneity in mPFC/PCC functional organization. Here we used cortical surface-based meta-analysis to identify a parcel in human PCC that was more strongly associated with the DN than with valuation effects. We then used resting-state fMRI data and a data-driven network analysis algorithm, spectral partitioning, to partition mPFC and PCC into “DN” and “non-DN” subdivisions in individual participants (n = 100 from the Human Connectome Project). The spectral partitioning algorithm identified individual-level cortical subdivisions that varied markedly across individuals, especially in mPFC, and were reliable across test/retest datasets. Our results point toward new strategies for assessing whether distinct cognitive functions engage common or distinct mPFC subregions at the individual level.

Highlights

The topography of Default Network cortical regions varies across individuals.

A community detection algorithm, spectral partitioning, was applied to rs-fMRI data.

The algorithm identified individualized Default Network regions in mPFC and PCC.

Default Network topography varied across individuals in mPFC, moreso than in PCC.

Overlap of task effects with DN regions should be assessed at the individual level.
Automated cryo-EM sample preparation by pin-printing and jet vitrification
Authors: Ravelli Raimond B.G. , Nijpels Frank J.T. , Henderikx Rene J.M. , Weissenberger Giulia , Thewessem Sanne , Gijsbers Abril , Beulen Bart W.A.M.M. , López-Iglesias Carmen , Peters Peter J.
Published: May 2019

The increasing demand for cryo-electron microscopy (cryo-EM) reveals drawbacks in current sample preparation protocols, such as sample waste and lack of reproducibility. Here, we present several technical developments that provide controlled and efficient sample preparation for cryo-EM studies. Pin printing substantially reduces sample waste by depositing only a sub-nanoliter volume of sample on the carrier surface. Sample evaporation is mitigated by dewpoint control feedback loops. The deposited sample is vitrified by jets of cryogen followed by submersion into a cryogen bath. Because the cryogen jets cool the sample from the center, premounted autogrids can be used and loaded directly into automated cryo-EMs. We integrated these steps into a single device, named VitroJet. The device’s performance was validated by resolving 4 standard proteins (apoferritin, GroEL, worm hemoglobin, beta-galactosidase) to ~3 Å resolution using a 200-kV electron microscope. The VitroJet offers a promising solution for improved automated sample preparation in cryo-EM studies.
The Human Dynamic Clamp reveals the fronto-parietal network linking real-time social coordination and cognition
Authors: Dumas G. , Moreau Q. , Tognoli E. , Kelso J.A.S.
Published: May 2019

How does the brain allow us to interact with others, and above all how does it handle situations when the goals of the interactors overlap (i.e. cooperation) or differ (i.e. competition)? Social neuroscience has already provided some answers to these questions but has tended to treat high-level, cognitive interpretations of social behavior separately from the sensorimotor mechanisms upon which they rely. The goal here is to identify the underlying neural processes and mechanisms linking sensorimotor coordination and intention attribution. We combine the Human Dynamic Clamp (HDC), a novel paradigm for studying realistic social behavior between self and other in well-controlled laboratory conditions, with high resolution electroencephalography (EEG). The collection of humanness and intention attribution reports, kinematics and neural data affords an opportunity to relate brain activity to the behavior of the HDC as well as to what the human is doing. Behavioral results demonstrate that sensorimotor coordination influences judgements of cooperativeness and humanness. Analysis of brain dynamics reveals two distinct networks related to integration of visuo-motor information from self and other. The two networks overlap over the right parietal region, an area known to be important for interpersonal motor interactions. Furthermore, connectivity analysis highlights how the judgement of humanness and cooperation of others modulate the connection between the right parietal hub and prefrontal cortex. These results reveal how distributed neural dynamics integrates information from ‘low-level’ sensorimotor mechanisms and ‘high-level’ social cognition to support the realistic social behaviors that play out in real time during interactive scenarios.

Significance Statement

Daily social interactions require us to coordinate with others and to reflect on their potential motives. This study investigates the brain and behavioral dynamics of these two key aspects of social cognition. Combining high-density electroencephalography and the Human Dynamic Clamp (a Virtual Partner endowed with human-based coordination dynamics), we show first, that several features of sensorimotor coordination influence attribution of intention and judgement of humanness; second, that the right parietal lobe is a key integration hub between information related to self- and other-behavior; and third, that the posterior online social hub is functionally coupled to anterior offline brain structures to support mentalizing about others. Our results stress the complementary nature of low-level and high-level mechanisms that underlie social cognition.
Resolving kinesin stepping: one head at a time
Authors: Stepp Willi L. , Ökten Zeynep
Published: May 2019

Kinesins are well-known to power diverse long-range transport processes in virtually all eukaryotic cells. The ATP-dependent processive stepping as well as the regulation of kinesin’ activity have thus been focus of extensive studies over the past decades. It is widely accepted that kinesin motors can self-regulate their activity by suppressing the catalytic activity of the ‘heads’. The distal random coil at the C-terminus, termed ‘tail domain’, is proposed to mediate this autoinhibition, however, a direct regulatory influence of the tail on the processive stepping of kinesin proved difficult to capture. Here, we simultaneously tracked the two distinct head domains in the kinesin-2 motor using dual-color super resolution microscopy (dcFIONA) and reveal for the first time their individual properties during processive stepping. We show that the autoinhibitory wild type conformation selectively impacts one head in the heterodimer but not the other. Our results provide key insights into the regulated kinesin stepping that had escaped experimental scrutiny.
Evolution in action: Habitat-transition leads to genome-streamlining in Methylophilaceae (Betaproteobacteriales)
Authors: Salcher Michaela M. , Schaefle Daniel , Kaspar Melissa , Neuenschwander Stefan M. , Ghai Rohit
Published: May 2019

The most abundant aquatic microbes are small in cell and genome size. Genome-streamlining theory predicts gene loss caused by evolutionary selection driven by environmental factors, favouring superior competitors for limiting resources. However, evolutionary histories of such abundant, genome-streamlined microbes remain largely unknown. Here we reconstruct the series of steps in the evolution of some of the most abundant genome-streamlined microbes in freshwaters (‘Ca. Methylopumilus’) and oceans (marine lineage OM43). A broad genomic spectrum is visible in the family Methylophilaceae (Betaproteobacteriales), from sediment microbes with medium-sized genomes (2-3 Mbp genome size), an occasionally blooming pelagic intermediate (1.7 Mbp), and the most reduced pelagic forms (1.3 Mbp). We show that a habitat transition from freshwater sediment to the relatively oligotrophic pelagial was accompanied by progressive gene loss and adaptive gains. Gene loss has mainly affected functions not necessarily required or advantageous in the pelagial or are encoded by redundant pathways. Likewise, we identified genes providing adaptations to oligotrophic conditions that have been transmitted horizontally from pelagic freshwater microbes. Remarkably, the secondary transition from the pelagial of lakes to the oceans required only slight modifications, i.e., adaptations to higher salinity, gained via horizontal gene transfer from indigenous microbes. Our study provides first genomic evidence of genome-reduction taking place during habitat transitions. In this regard, the family Methylophilaceae is an exceptional model for tracing the evolutionary history of genome-streamlining as such a collection of evolutionarily related microbes from different habitats is practically unknown for other similarly abundant microbes (e.g., ‘Ca. Pelagibacterales’, ‘Ca. Nanopelagicales’).
Fast quantification of uncertainty in non-linear diffusion MRI models for artifact detection and more power in group studies
Authors: Harms R.L. , Fritz F.J. , Schoenmakers S. , Roebroeck A.
Published: May 2019

Diffusion MRI (dMRI) allows for non-invasive investigation of brain tissue microstructure. By fitting a model to the dMRI signal, various quantitative measures can be derived from the data, such as fractional anisotropy, neurite density and axonal radii maps. The uncertainty in these dMRI measures is often ignored, while previous work in functional MRI has shown that incorporating uncertainty estimates can lead to group statistics with a higher statistical power. We propose the Fisher Information Matrix (FIM) as a generally applicable method for quantifying the parameter uncertainties in non-linear diffusion MRI models. In direct comparison with Markov Chain Monte Carlo sampling, the FIM produces similar uncertainty estimates at lower computational cost. Using acquired and simulated data, we then list several characteristics that influence the parameter variances, like data complexity and signal-to-noise ratio. In individual subjects, the parameter standard deviations can help in detecting white matter artifacts as patches of relatively large standard deviations. In group statistics, we recommend using the parameter standard deviations by means of variance weighted averaging. Doing so can reduce the overall variance in group statistics and reduce the effect of data artifacts without discarding data from the analysis. Both these effects can lead to a higher statistical power in group studies.
High-throughput smFRET analysis of freely diffusing nucleic acid molecules and associated proteins
Authors: Segal Maya , Ingargiola Antonino , Lerner Eitan , Chung Sang Yoon , White Jonathan A. , Streets Aaron , Weiss S. , Michalet X.
Published: May 2019

Single-molecule Förster resonance energy transfer (smFRET) is a powerful technique for nanometer-scale studies of single molecules. Solution-based smFRET, in particular, can be used to study equilibrium intra- and intermolecular conformations, binding/unbinding events and conformational changes under biologically relevant conditions without ensemble averaging. However, single-spot smFRET measurements in solution are slow. Here, we detail a high-throughput smFRET approach that extends the traditional single-spot confocal geometry to a multispot one. The excitation spots are optically conjugated to two custom silicon single photon avalanche diode (SPAD) arrays. Two-color excitation is implemented using a periodic acceptor excitation (PAX), allowing distinguishing between singly- and doubly-labeled molecules. We demonstrate the ability of this setup to rapidly and accurately determine FRET efficiencies and population stoichiometries by pooling the data collected independently from the multiple spots. We also show how the high throughput of this approach can be used to increase the temporal resolution of single-molecule FRET population characterization from minutes to seconds. Combined with microfluidics, this high-throughput approach will enable simple real-time kinetic studies as well as powerful molecular screening applications.
Motor axon excitability measures in the rat tail are the same awake or anaesthetized using sodium pentobarbital
Authors: Jones Kelvin E , Bennett David J
Published: May 2019

Background

Nerve excitability tests in sciatic motor axons are sensitive to anaesthetic choice. Results using ketamine/xylazine (KX) are different from those using sodium pentobarbital (SP). It is not clear which results are most similar to the awake condition, though results using SP appear more similar to human results.

Methods

Nerve excitability in tail motor axons was tested in 8 adult female rats with a chronic sacral spinal cord injury. These animals have no behavioural response to electrical stimulation of the tail and were tested awake and then anaesthetized using SP.

Results

The nerve excitability test results in the awake condition were indistinguishable from the results when the same rats were anaesthetized with sodium pentobarbital. Summary plots of the test results overlap within the boundaries of the standard error and paired t-tests on the 42 discrete measures generated by nerve excitability testing yielded no significant differences (after Bonferroni correction for multiple comparisons).

Conclusions

Nerve excitability test results in rat motor axons are the same whether the animals are awake or anesthetized using sodium pentobarbital.
Spectral clustering in regression-based biological networks
Authors: Gaynor Sheila M. , Lin Xihong , Quackenbush John
Published: May 2019

Biological networks often have complex structure consisting of meaningful clusters of nodes that are integral to understanding biological function. Community detection algorithms to identify the clustering, or community structure, of a network have been well established. These algorithms assume that data used in network construction is observed without error. However, oftentimes intermediary analyses such as regression are performed before constructing biological networks and the associated error is not propagated in community detection. In expression quantitative trait loci (eQTL) networks, one must first map eQTLs via linear regression in order to specify the matrix representation of the network. We study the effects of using estimates from regression models when applying the spectral clustering approach to community detection. We demonstrate the impacts on the affinity matrix and consider adjusted estimates of the affinity matrix for use in spectral clustering. We further provide a recommendation for selection of the tuning parameter in spectral clustering. We evaluate the proposed adjusted method for performing spectral clustering to detect gene clusters in eQTL data from the GTEx project and to assess the stability of communities in biological data.
Identifying miRNA synergism using multiple-intervention causal inference
Authors: Zhang Junpeng , Pham Vu Viet Hoang , Liu Lin , Xu Taosheng , Truong Buu , Li Jiuyong , Rao Nini , Le Thuc Duy
Published: May 2019

Background

Studying multiple microRNAs (miRNAs) synergism in gene regulation could help to understand the regulatory mechanisms of complicated human diseases caused by miRNAs. Several existing methods have been presented to infer miRNA synergism. Most of the current methods assume that miRNAs with shared targets at the sequence level are working synergistically. However, it is unclear if miRNAs with shared targets are working in concert to regulate the targets or they individually regulate the targets at different time points or different biological processes. A standard method to test the synergistic activities is to knock-down multiple miRNAs at the same time and measure the changes in the target genes. However, this approach may not be practical as we would have too many sets of miRNAs to test.

Results

In this paper, we present a novel framework called miRsyn for inferring miRNA synergism by using a causal inference method that mimics the multiple-intervention experiments, e.g. knocking-down multiple miRNAs, with observational data. Our results show that several miRNA-miRNA pairs that have shared targets at the sequence level are not working synergistically at the expression level. Moreover, the identified miRNA synergistic network is small-world and biologically meaningful, and a number of miRNA synergistic modules are significantly enriched in breast cancer. Our further analyses also reveal that most of synergistic miRNA-miRNA pairs show the same expression patterns. The comparison results indicate that the proposed multiple-intervention causal inference method performs better than the single-intervention causal inference method in identifying miRNA synergistic network.

Conclusions

Taken together, the results imply that miRsyn is a promising framework for identifying miRNA synergism, and it could enhance the understanding of miRNA synergism in breast cancer.
Structure of a hyperthermostable dimeric archaeal Rubisco fromHyperthermus butylicus
Authors: Bundela Rudranuj , Keown Jeremy , Watkin Serena , Pearce Frederick Grant
Published: May 2019

The crystal structure of ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) from the hyperthermophilic archaeonHyperthermus butylicusis presented at 1.8 Å resolution. Previous structures of archaeal Rubisco have been found to assemble into decamers, and this oligomerization was thought to be required for a highly thermally stable enzyme. In the current study,H. butylicusRubisco is shown to exist as a dimer in solution, yet has a thermal denaturation midpoint of 114°C, suggesting that high thermal stability can be achieved without an increased oligomeric state. This increased thermal stability appears to be due to an increased number of electrostatic interactions within the monomeric subunit. As such,H. butylicusRubisco presents a well characterized system in which to investigate the role of assembly and thermal stability in enzyme function.
Inertia parameter identification of anunknown captured space target
Authors: Liu Xiaofeng , Zhou Bangzhao , Xiao Boyang , Cai Guoping
Published: May 2019

Purpose

The purpose of this paper is to present a method to obtain the inertia parameter of a captured unknown space target.

Design/methodology/approach

An inertia parameter identification method is proposed in the post-capture scenario in this paper. This method is to resolve parameter identification with two steps: coarse estimation and precise estimation. In the coarse estimation step, all the robot arms are fixed and inertia tensor of the combined system is first calculated by the angular momentum conservation equation of the system. Then, inertia parameters of the unknown target are estimated using the least square method. Second, in the precise estimation step, the robot arms are controlled to move and then inertia parameters are once again estimated by optimization method. In the process of optimization, the coarse estimation results are used as an initial value.

Findings

Numerical simulation results prove that the method presented in this paper is effective for identifying the inertia parameter of a captured unknown target.

Practical implications

The presented method can also be applied to identify the inertia parameter of space robot.

Originality/value

In the classic momentum-based identification method, the linear momentum and angular momentum of system, both considered to be conserved, are used to identify the parameter of system. If the elliptical orbit in space is considered, the conservation of linear momentum is wrong. In this paper, an identification based on the conservation of angular momentum and dynamics is presented. Compared with the classic momentum-based method, this method can get a more accurate identification result.
Abandon canon in American sociology
Authors: Au Anson
Published: May 2019

Purpose

The purpose of this paper is to challenge the practice of having, using and constructing any canon in sociological theory. This paper argues that the elitism of American sociology and the forms of inequality it engenders are sustained by the construction of a canon itself.

Design/methodology/approach

This paper adopts a conceptual approach to examine the problems of research practice, academic writing, inequality and empirical translation that canonical thinking engenders within the academy and beyond.

Findings

Reflecting on the problems outlined, this paper articulates a more democratic agenda for treating canon in research and education by drawing upon standards of practice in ethnography, participatory action research and Southern Theory.

Originality/value

This paper interrogates the relations of domination that remain at work in the discipline and that which concern the elite position of American sociology itself.
Social networks, accessed and mobilised social capital and the employment status of older workers
Authors: Gayen Kaberi , Raeside Robert , McQuaid Ronald
Published: May 2019

Purpose

The purpose of this paper is to demonstrate the importance of social networks, and the social capital embedded in them, to secure employment if someone had become unemployed after the age of 50 years and to reveal the process of accessing and mobilising that social capital.

Design/methodology/approach

A case study of a Scottish labour market was undertaken which involved an interview-based survey of those who became unemployed in their early 50’s and tried to regain employment. The interview had structured and unstructured parts which allowed both quantitative and qualitative analysis to compare those who were successful in regaining work with those who were not. The uniqueness of the paper is the use of social network components while controlling for other socio-economic and demographic variables in job search of older workers.

Findings

Those older people who were unemployed and, returned to employment (reemployed) had a higher proportion of contacts with higher prestige jobs, their job searching methods were mainly interpersonal and the rate of finding their last job via their social networks was higher than those who remained unemployed. Both groups mobilised social capital (MSC), but those reemployed accessed higher “quality” social capital. “Strong ties”, rather than “weak ties”, were found to be important in accessing and mobilising social capital for the older workers who returned to employment.

Research limitations/implications

This work is limited to a local labour market and is based on a small but informative sample. However, it does show that policy is required to allow older people to enhance their social networks by strengthening the social capital embedded in the networks. The results support the use of intermediaries as bridges to help compensate for older people who have weak social networks. Besides the policy implications, the paper also has two distinct research implications. First, the use of social network component to the existing literature of older workers’ job search. Second, exploring the type and relational strength with network members to explain older workers’ reemployment.

Practical implications

The paper illustrates that how accessed and MSC can be measured.

Social implications

As populations age, this work points to an approach to support older people to re-enter employment and to include them in society.

Originality/value

The paper extends social network and employment literature to fill gaps on how older people require to both access and mobilise social capital. The importance of “strong ties” in the reemployment of older workers contrasts with much of the literature on younger workers where the “strength of weak ties” so far has been regarded as essential for successful job search. Measures are forwarded to reveal the relevance of social capital. The policy value of the work is in suggesting ways to facilitate older people re-enter or remain in work and hence sustain their well-being.
Differences in organization citizenship behavior between “serumpun” countries (Indonesia – Malaysia)
Authors: Suharnomo Suharnomo , Hashim Fathyah
Published: May 2019

Purpose

This paper aims to examine the effect of job motivation and commitment on organizational citizenship behavior (OCB) of Indonesian and Malaysian employees. Organizational and national cultures are introduced as moderators and OCB as a mediator to investigate their relationships in the context of job performance.

Design/methodology/approach

The sample was drawn from employees using a purposive sampling method. A total of 264 valid questionnaires were obtained from employees. The data were analyzed using regression analysis.

Findings

The results show that job commitment and job motivation positively affect OCB in Indonesia but not Malaysia. The results also reveal that job motivation affects OCB in both countries. In Indonesia, organizational culture and national culture partially moderate the influence of job commitment and motivation on OCB, except the commitment to the organization's culture. However, roles of these moderators in job commitment and motivation are not evident in Malaysia. The result of this study also shows that OCB affects performance in Malaysia but not Indonesia.

Practical implications

The results of this study can be used to explore Indonesian and Malaysian employees. Although the culture of these two countries is originated from the same roots which cause many similarities among them, there are differences in terms of OCB and employee’s performance that can affect organizational performance and also ways in dealing business with Indonesian and Malaysian companies.

Originality/value

This study is one of the first studies to examine cross-cultural dimensions in two Southeast Asian countries. The findings contribute to the current OCB literature by confirming the roles of OCB and culture in the effects of job motivation and commitment on job performance.
Curvilinear relationship between intra-team trust and team innovation: the moderating role of task complexity
Authors: Hendarsjah Hidajat , Susanto Ely , Lies Sugianto Bambang Riyanto , Handoko Tarsisius Hani
Published: May 2019

Purpose

This paper aims to identify the relationship pattern between intra-team trust and team innovation and the influence of moderating variable task complexity on the relationship. It also describes why and how intra-team trust is a unique antecedent for team innovation, as too much or too less influence of the variable can have detrimental effects on team innovation.

Design/methodology/approach

The paper uses survey research. The data were collected by distributing questionnaires to work teams. After the individual-level data were aggregated into team-level data, hierarchical linier regression was conducted to test the hypotheses.

Findings

The paper provides empirical findings that (1) intra-team trust and team innovation have a curvilinear relationship pattern, (2) task complexity does not influence curvilinear relationship (3) and the increase in task complexity improves the possibility of team innovation to occur.

Research limitations/implications

The paper has two limitations. First, as intra-team trust was also represented by aggregated perception of team members’ trust for outside parties (not only members’ perception for their teams), the future research is expected to include the representation in the instrument. Second, recent research studies have shown that contextual factor of task interdependence, instead of task complexity, also had an effect on the relationship pattern between intra-team trust and team performance (i.e. team innovation). Therefore, for future researchers, it is suggested that the use of task interdependence would be an alternative moderating variable on the relationship between intra-team trust and team innovation.

Practical implications

The paper discusses the strategy to enhance team innovation by revealing strategies to manage interplay among intra-team trust, team complexity and the desired team innovation.

Originality/value

The paper identifies the need to conduct empirical research on how an interplay among intra-team trust, task complexity and team innovation could be enabled.
Rethinking on growth mechanism of Indian sugar industry
Authors: Sheetal  , Kumar Rajiv
Published: May 2019

Purpose

The purpose of this paper is to revisit the growth mechanism of Indian sugar industry by deploying quantitative and qualitative metaphors.

Design/methodology/approach

The research paper has been composed through comprehensive primary research survey using a structured questionnaire, and qualitative discussion following semi- structured interviews with industry professionals on emerging issues across the whole value chain of sugar industry. Respondents regarding primary survey were selected using the purposive sampling, and this collected quantitative information has been verified on the lenses of multiple stream modelling (MSM).

Findings

To support the data analysis, MSM – a policy-making framework has been developed which found that government being a central construct exerts a profound presence across whole value chain; in suppliers’ mechanism, marketing of sugar and sugar mills’ infrastructural expansions. Nationwide uniformity in sugar policy instead of states’ monopolistic policies, rational and mutual benefits-based decisions collectively by the government, mills management and sugarcane growers, and diversification in production processes are enumerated as the proposed solutions against the chronical industry problems.

Practical implications

This study enriches extant Asian sugar industry literature. For policymakers, the proposed results should be of help in identifying specific policies to support the competitiveness of local systems and individual manufacturing companies in the Indian sugar industry suggesting that the development of growth mechanisms can contribute simultaneously to improve the financial, market and operational performance of both individual firms and supply chains.

Originality/value

Cyclicality in production, rising sugarcane farmers’ problems and resulting severe financial distress of mills are some of the topical issues of Indian sugar industry, and the study has explored these issues factually, quantitatively and qualitatively in proximity of industry professionals and described in this depository with the help of document analysis.
Understanding customer-perceived quality in informal stores
Authors: Osakwe Christian Nedu
Published: May 2019

Purpose

Although customer-perceived quality (CPQ) has been studied for years, very little is known about the implications of CPQ to informal retail stores particularly in collectivist and high uncertainty avoidance societies like Nigeria. More specifically, this study aims to investigate the indirect implications of CPQ to post-purchase behaviour primarily word-of-mouth (WoM) communication which is even more critical for customer acquisition in the research context. By so doing, it develops a contextualised model in which the emerging concept of commercial friendship (CF) is incorporated to mediate the relationship between CPQ and WoM communication.

Design/methodology/approach

Using a survey-based design, data were gathered from 372 informal merchants’ customers. Structural equation modelling technique primarily PLS-SEM (partial least squares structural equation modelling) was used in analysing the data.

Findings

The data confirm that the multifaceted CPQ construct has an important implication for WoM through the mediation of CF. Supplementary analysis reveals that CF fully mediates one of the sub-components of CPQ, namely, personal interaction in relationship to WoM in addition to acting as a partial mediator between store policy, physical aspect and reliability and WoM.

Originality/value

The value of this study is that it draws attention to the special role that CF plays in the investigation of the relationship between CPQ and WoM communication in the research context. Additionally, it is a step towards extending and contextualising research about service quality perceptions and its outcomes in non-traditional Western contexts.
Claimants’ views on total and permanent disability insurance claims
Authors: Black Margaret Elizabeth , Matthews Lynda Roslyn , Millington Michael J.
Published: May 2019

Purpose

This study aims to investigate Australian claimants’ experience of the total and permanent disability (TPD) insurance claims process and documents their recommendations for improvement.

Design/methodology/approach

A qualitative methodology was used. In all, 12 claimants with finalized TPD claims were recruited via their superannuation fund. Data collected from in-depth interviews were thematically analyzed and reported using the COREQ checklist. Extracts from verbatim transcription were included to represent the claimant without bias.

Findings

Most interviewees described a flawed claims process in which important information was withheld or unclear, procedures were complicated and arduous, communication was poor and frequent need for “chasing up” was frustrating. The claims process undermined the well-being of many interviewees at a critical time in their adjustment to disability. Lump sum payment yielded unexpected consequences for ten interviewees. Some interviewees retained a desire to work despite serious disability.

Research limitations/implications

The use of purposive sampling means that findings may not represent the experience of all claimants with finalized TPD claims. Saturation of knowledge was reached despite the relatively small number of in-depth interviews conducted. In the absence of previous research, this study identifies areas of concern in the TPD claimant experience and posits a set of important claimant issues for further investigation.

Practical implications

A person-centred approach is needed. Claimants would benefit from introduction of clear process information, a single point-of-contact throughout claim, advocacy/support and rehabilitation.

Originality/value

This inaugural study provides an understanding of challenges faced by TPD claimants. All interviewees provided suggestions for improvement in the TPD claims process.
Insights into VdCmr1‐mediated protection against high temperature stress and UV irradiation in Verticillium dahliae
Authors: Fang Yulin , Klosterman Steven J. , Tian Chengming , Wang Yonglin
Published: May 2019

The fungus Verticillium dahliae causes vascular wilt disease on more than 200 plant species worldwide. This fungus can survive for years in soil as melanized microsclerotia. We found that VdCmr1, a transcription factor, is required for the melanin production and increased survival following UV irradiation in V. dahliae but not for microsclerotia production or virulence. Here, we provided evidence how VdCmr1 protects against high temperature (HT) and UV irradiation in V. dahliae. The results indicate that VdCmr1 mediates entry to the diapause period in V. dahliae in response to HT and contributes to the expression of proteins to minimize protein misfolding and denaturation. VdCmr1 deletion results in the misregulation of DNA repair machinery, suggestive of reduced DNA repair capacity following UV irradiation and in correlation with the low survival rate of UV‐treated VdCmr1 mutants. We discovered a putative VdCmr1‐dependent gene cluster associated with secondary metabolism and stress responses. We also functionally characterized two VdCmr1‐responsive genes participating in HT and UV response. These results shed further light on the roles of VdCmr1 in protection from HT or UV irradiation, and the additional insights into the mechanisms of this protection may be useful to exploit for more effective disease control.