bluuebunny/crossref_metadata_2025_split huggingface dataset:
Disrupted reinforcement learning during post-error slowing in ADHD
Authors: Chevrier Andre , Bhaijiwala Mehereen , Lipszyc Jonathan , Cheyne Douglas , Graham Simon , Schachar Russell 
Published: October 2018

AbstractADHD is associated with altered dopamine regulated reinforcement learning on prediction errors. Despite evidence of categorically altered error processing in ADHD, neuroimaging advances have largely investigated models of normal reinforcement learning in greater detail. Further, although reinforcement leaning critically relies on ventral striatum exerting error magnitude related thresholding influences on substantia nigra (SN) and dorsal striatum, these thresholding influences have never been identified with neuroimaging. To identify such thresholding influences, we propose that error magnitude related activities must first be separated from opposite activities in overlapping neural regions during error detection. Here we separate error detection from magnitude related adjustment (post-error slowing) during inhibition errors in the stop signal task in typically developing (TD) and ADHD adolescents using fMRI. In TD, we predicted that: 1) deactivation of dorsal striatum on error detection interrupts ongoing processing, and should be proportional to right frontoparietal response phase activity that has been observed in the SST; 2) deactivation of ventral striatum on post-error slowing exerts thresholding influences on, and should be proportional to activity in dorsal striatum. In ADHD, we predicted that ventral striatum would instead correlate with heightened amygdala responses to errors. We found deactivation of dorsal striatum on error detection correlated with response-phase activity in both groups. In TD, post-error slowing deactivation of ventral striatum correlated with activation of dorsal striatum. In ADHD, ventral striatum correlated with heightened amygdala activity. Further, heightened activities in locus coeruleus (norepinephrine), raphe nucleus (serotonin) and medial septal nuclei (acetylcholine), which all compete for control of DA, and are altered in ADHD, exhibited altered correlations with SN. All correlations in TD were replicated in healthy adults. Results in TD are consistent with dopamine regulated reinforcement learning on post-error slowing. In ADHD, results are consistent with heightened activities in the amygdala and non-dopaminergic neurotransmitter nuclei preventing reinforcement learning.
Apicomplexan motility depends on the operation of an endocytic-secretory cycle
Authors: Gras Simon , Jimenez-Ruiz Elena , Klinger Christen M. , Lemgruber Leandro , Meissner Markus 
Published: October 2018

ABSTRACTApicomplexan parasites invade host cells in an active process, involving their ability to move by gliding motility and invasion. While the acto-myosin-system of the parasite plays a crucial role in the formation and release of attachment sites during this process, there are still open questions, such as how the force powering motility is generated. In many eukaryotes a secretory-endocytic cycle leads to recycling of receptors (integrins), necessary to form attachment sites, regulation of surface area during motility and generation of retrograde membrane flow. Here we demonstrate that endocytosis operates during gliding motility inToxoplasma gondiiand appears to be crucial for the establishment of retrograde membrane flow, since inhibition of endocytosis blocks retrograde flow and motility. We identified lysophosphatidic acid (LPA) as a potent stimulator of endocytosis and demonstrate that extracellular parasites can efficiently incorporate exogenous material, such as nanogold particles. Furthermore, we show that surface proteins of the parasite are recycled during this process. Interestingly, the endocytic and secretory pathways of the parasite converge, and endocytosed material is subsequently secreted, demonstrating the operation of an endocytic-secretory cycle. Together our data consolidate previous findings and we propose a novel model that reconciles parasite motility with observations in other eukaryotes: the fountain-flow-model for apicomplexan parasite motility.
Bayesian inference of metabolic kinetics from genome-scale multiomics data
Authors: St. John Peter C. , Strutz Jonathan , Broadbelt Linda J. , Tyo Keith E.J. , Bomble Yannick J. 
Published: October 2018

SummaryModern biological tools generate a wealth of data on metabolite and protein concentrations that can be used to help inform new strain designs. However, integrating these data sources to generate predictions of steady-state metabolism typically requires a kinetic description of the enzymatic reactions that occur within a cell. Parameterizing these kinetic models from biological data can be computationally difficult, especially as the amount of data increases. Robust methods must also be able to quantify the uncertainty in model parameters as a function of the available data, which can be particularly computationally intensive. The field of Bayesian inference offers a wide range of methods for estimating distributions in parameter uncertainty. However, these techniques are poorly suited to kinetic metabolic modeling due to the complex kinetic rate laws typically employed and the resulting dynamic system that must be solved. In this paper, we employ linear-logarithmic kinetics to simplify the calculation of steady-state flux distributions and enable efficient sampling and variational inference methods. We demonstrate that detailed information on the posterior distribution of kinetic model parameters can be obtained efficiently at a variety of different problem scales, including large-scale kinetic models trained on multiomics datasets. These results allow modern Bayesian machine learning tools to be leveraged in understanding biological data and developing new, efficient strain designs.
A comparison of visual features used by humans and machines to classify wildlife
Authors: Miao Zhongqi , Gaynor Kaitlyn M , Wang Jiayun , Liu Ziwei , Muellerklein Oliver , Norouzzadeh Mohammad Sadegh , Bowie Rauri C K , Nathan Ran , Yu Stella X , Getz Wayne M 
Published: October 2018

ABSTRACTIn our quest to develop more intelligent machines, knowledge of the visual features used by machines to classify objects shall be helpful. The current state of the art in training machines to classify wildlife species from camera-trap data is to employ convolutional neural networks (CNN) encoded within deep learning algorithms. Here we report on results obtained in training a CNN to classify 20 African wildlife species with an overall accuracy of 87.5% from a dataset containing 111,467 images. We then used a gradient-weighted class-activation-mapping (Grad-CAM) procedure to extract the most salient pixels in the final convolution layer. We show that these pixels highlight features in particular images that are in most, but not all, cases similar to those used to train humans to identify these species. Further, we used mutual information methods to identify the neurons in the final convolution layer that consistently respond most strongly across a set of images of one particular species, and we then interpret the features in the image where the strongest responses occur. We also used hierarchical clustering offeature vectors(i.e., the state of the final fully-connected layer in the CNN) associated with each image to produce avisual similarity dendrogramof identified species. Finally, we evaluated how images that were not part of the training set fell within our dendrogram when these images were one of the 20 species “known” to our CNN in contrast to where they fell when these images were “unknown” to our CNN.
Genomic variants concurrently listed in a somatic and a germline mutation database have implications for disease-variant discovery and genomic privacy
Authors: Meyerson William , Gerstein Mark 
Published: October 2018

AbstractBackgroundMutations arise in the human genome in two major settings: the germline and soma. These settings involve different inheritance patterns, chromatin structures, and environmental exposures, all of which might be predicted to differentially affect the distribution of substitutions found in these settings. Nonetheless, recent studies have found that somatic and germline mutation rates are similarly affected by endogenous mutational processes and epigenetic factors.ResultsHere, we quantified the number of single nucleotide variants that co-occur between somatic and germline call-sets (cSNVs), compared this quantity with expectations, and explained noted departures. We found that three times as many variants are shared between the soma and germline than is expected by independence. We developed a new, general-purpose statistical framework to explain the observed excess of cSNVs in terms of the varying mutation rates of different kinds substitution types and of genomic regions. Using this metric, we find that more than 90% of this excess can be explained by our observation that the basic substitution types (such as N[C->T]G, C->A, etc.) have correlated mutation rates in the germline and soma. Matched-normal read depth analysis suggests that an appreciable fraction of this excess may also derive from germline contamination of somatic samples.ConclusionOverall, our results highlight the commonalities in substitution patterns between the germline and soma. The universality of some aspects of human mutation rates offers insight into the potential molecular mechanisms of human mutation. The highlighted similarities between somatic and germline mutation rates also lay the groundwork for future studies that distinguish disease-causing variants from a genomic background informed by both somatic and germline variant data. Moreover, our results also indicate that the depth of matched normal sequencing necessary to ensure genomic privacy of donors of somatic samples may be higher than previously appreciated. Furthermore, the fact that we were able to explain such a high portion of recurrent variants using known determinants of mutation rates is evidence that the genomics community has already discovered the most important predictors of mutation rates for single nucleotide variants.
Metabolome-scale genome-wide association studies reveal chemical diversity and genetic control of maize specialized metabolites
Authors: Shaoqun Zhou , Kremling Karl A. , Nonoy Bandillo , Annett Richter , Zhang Ying K. , Ahern Kevin R. , Artyukhin Alexander B. , Hui Joshua X. , Schroeder Frank C. , Buckler Edward S. , Georg Jander 
Published: October 2018

One Sentence SummaryHPLC-MS metabolite profiling of maize seedlings, in combination with genome-wide association studies, identifies numerous quantitative trait loci that influence the accumulation of foliar metabolites.AbstractCultivated maize (Zea mays) retains much of the genetic and metabolic diversity of its wild ancestors. Non-targeted HPLC-MS metabolomics using a diverse panel of 264 maize inbred lines identified a bimodal distribution in the prevalence of foliar metabolites. Although 15% of the detected mass features were present in >90% of the inbred lines, the majority were found in <50% of the samples. Whereas leaf bases and tips were differentiated primarily by flavonoid abundance, maize varieties (stiff-stalk, non-stiff-stalk, tropical, sweet corn, and popcorn) were differentiated predominantly by benzoxazinoid metabolites. Genome-wide association studies (GWAS), performed for 3,991 mass features from the leaf tips and leaf bases, showed that 90% have multiple significantly associated loci scattered across the genome. Several quantitative trait locus hotspots in the maize genome regulate the abundance of multiple, often metabolically related mass features. The utility of maize metabolite GWAS was demonstrated by confirming known benzoxazinoid biosynthesis genes, as well as by mapping isomeric variation in the accumulation of phenylpropanoid hydroxycitric acid esters to a single linkage block in a citrate synthase-like gene. Similar to gene expression databases, this metabolomic GWAS dataset constitutes an important public resource for linking maize metabolites with biosynthetic and regulatory genes.
Analysis of natural fibre composites for aerospace structures
Authors: Brischetto Salvatore 
Published: October 2018

Purpose
The main idea is the comparison between composites including natural fibres (such as the linoleum fibres) and typical composites including carbon fibres or glass fibres. The comparison is proposed for different structures (plates, cylinders, cylindrical and spherical shells), lamination sequences (cross-ply laminates and sandwiches with composite skins) and thickness ratios. The purpose of this paper is to understand if linoleum fibres could be useful for some specific aerospace applications.

Design/methodology/approach
A general exact three-dimensional shell model is used for the static analysis of the proposed structures to obtain displacements and stresses through the thickness. The shell model is based on a layer-wise approach and the differential equations of equilibrium are solved by means of the exponential matrix method.

Findings
In qualitative terms, composites including linoleum fibres have a mechanical behaviour similar to composites including glass or carbon fibres. In terms of stress and displacement values, composites including linoleum fibres can be used in aerospace applications with limited loads. They are comparable with composites including glass fibres. In general, they are not competitive with respect to composites including carbon fibres. Such conclusions have been verified for different structure geometries, lamination sequences and thickness ratios.

Originality/value
The proposed general exact 3D shell model allows the analysis of different geometries (plates and shells), materials and laminations in a unified manner using the differential equilibrium equations written in general orthogonal curvilinear coordinates. These equations written for spherical shells degenerate in those for cylinders, cylindrical shell panels and plates by means of opportune considerations about the radii of curvature. The proposed shell model allows an exhaustive comparison between different laminated and sandwich composite structures considering the typical zigzag form of displacements and the correct imposition of compatibility conditions for displacements and equilibrium conditions for transverse stresses.
Experimental and artificial neural network investigation on the effect of inclination angle on the interface temperature of CPU/metal foam heat sink
Authors: Rashidi Ali Mohammad , Paknezhad Mehrad , Yousefi Tooraj 
Published: October 2018

Purpose
This study aims to clarify the relationship between inclination angle of hot surface of CPU and its temperature in absence and presence of aluminum foam as a cooling system. It proposes application of the artificial neural [multi-layer perceptron (MLP) and radial basis function] networks and adaptive neuron-fuzzy inference system (ANFIS) to predict interface temperature of central processing unit (CPU)/metal foam heat sink.

Design/methodology/approach
To provide a consistent set of data, the surface of an aluminum cone with and without installing Duocel aluminum foam was heated in a natural convection using an electrical resistor. The hot surface temperature was measured using five K-type thermocouples (±0.1°C). To develop the predictive models, ambient temperature, input power and inclination angle are taken as input which varied from 23°C to 32°C, 4 to 20 W and 0° to 90°, respectively. The hot surface temperature is taken as the output.

Findings
The results show that in the presence of foam, the hot surface temperature was less sensitive to the variations of angle, and the maximum enhancement of the heat transfer coefficient was 23 per cent at the vertical position. Both MLP network and ANFIS are comparable, but the values predicted by MLP network are in more conformity with the measured values.

Originality/value
The effect of metal foam on the inclination angle/hot surface temperature dependence is identified. The optimum angle is clarified. The applicability of the MLP networks to predict interface temperature of CPU/heat sink is approved.
Time management: presenteeism versus management-by-objectives
Authors: Amponsah-Tawiah Kwesi , Opata John Louis , Tetteh Samuel Doku 
Published: October 2018

Purpose
This study examined the actual productive hours of employees from the service sector in Ghana.

Design/methodology/approach
This study adopted an exploratory cross-sectional survey design. The purposive and convenience sampling techniques were used to identify the service organizations and recruited 520 employees in Accra for the study. Specifically, these respondents were workers from banks, insurance companies, auditing firms and oil and gas companies. The data were analyzed using frequencies and other descriptive statistics.

Findings
Results showed poor time management among the study organizations. It was reported that although most workers report to work as early as 6:30 a.m., they wait until 8:30 a.m. to commence the day’s work schedule. In addition, they start thinking of break at least 15 min before actual break time which decreases productivity. In addition, employees reported spending at least 30 min on break. They also added that, they start clearing the desks about 15 min before actual closing time and leave the office at exactly 5:00 p.m.

Practical Implications
This study shows that the physical presence of workers does not necessarily mean they are working. The study proposes an alternative way to increase productivity rather than relying on physical presence of the workers.

Originality/value
This study is among the few that empirically sought to explore the actual time that workers use in a day at work. Thus, it measured actual productive hours at of service employees in Ghana.
Assessment of revenue efficiency of Indian scheduled commercial banks
Authors: Bhatia Aparna , Mahendru Megha 
Published: October 2018

Purpose
This paper aims to endeavour to assess revenue efficiency (RE) scores of Scheduled Commercial Banks operating in India. Differences in RE are studied across varying ownership as well. The study also determines the nature of return to scale of Indian SCBs as whole as well as classified across ownership. Number of banks operating as leaders and laggards has also been calculated.

Design/methodology/approach
RE of banks is calculated by using the non-parametric approach, namely, data envelopment analysis (DEA). Further, the differences in the efficiency scores are examined by applying Panel Tobit Regression.

Findings
The results of DEA suggest that none of the banks has ever achieved full RE score of 1 in any of the years under study. An inconsistent pattern of RE is seen. Private sector banks have performed better than their counterparts in public and foreign sector. Maximum number of banks operating on decreasing return to scale are from public sector, and the highest number of banks operating on constant return to scale belong to Foreign Sector. More number of banks operates as laggards in the Indian financial system. Thus, there still exists room for improvement for banks in all sectors.

Originality/value
With specific reference to India, less empirical work has been carried out with respect to RE. As only two studies so far from the literature are available that consider RE exclusively, namely, Ram Mohan and Ray (2004) and Bhatia and Mahendru (2015). However, Ram Mohan and Ray (2004) considered only the reformatory phase, whereas Bhatia and Mahendru (2015) analyzed the performance for specific points of time only. None of the study has been able to give any concrete findings according to sector-wise performance of banks in terms of RE parameters.
The “Chancellor’s foot” and the contrivance of deportability in the UK: matters arising
Authors: Ikegwuruka Cosmas 
Published: October 2018

PurposeIt has been argued that the UK has the reputation of operating a complex set of immigration laws to the extent that the constantly changing laws and regulations lead much to confusion and lack of accountability. It has further been argued that the ever-increasing and shifting pattern of deportation laws (some of which are retroactive) violates the basic principles of human rights norms. This paper aims to raise the query as to whether legislation associated with deportation is constantly enacted and revised to achieve deportation without regard to the remit of the doctrine of legitimate expectation encapsulated under the principle of legal certainty.Design/methodology/approachThis research applies the doctrinal research methodology in addition to somewhat reliance on anecdotal evidence. Doctrinal research is library-based and reliance will be placed on primary and secondary materials such as legislations, case laws, soft laws on the one hand and textbooks, journals, articles, legal encyclopaedia, databases and many valuable websites on the other hand.FindingsWhile it is accepted that the State enjoys the discretion or prerogative to deport migrants that violate the State’s immigration laws, the author posits that the issue of constant changes breed uncertainty, which in turn breeds unpredictability leading to unaccountability. Drawing on the UK’s state practice, the author will submit that contrivance of deportability and/or removability is adumbrated by the legal production of migrant irregularity exemplified by inconsistent and uncertain laws that vary like the “Chancellor’s foot”. In addition, the research found that crimmigration heightened the velocity of deportation by expanding deportability grounds by way of triggering broader, harsher and more frequent criminal consequences leading to conviction, thereby creating a suitable avenue for deportation and reducing the scope for challenging deportation decisions.Originality/valueThe research is an original piece of work that contributes to scholarship and knowledge in the area of migration as it concerns international human rights law given that wider matters within the boundaries of immigration and nationality laws do have effect on individual possession of rights to be in the UK, by way of lawful presence or as a matter of discretion.
The largest financial groups from emerging economies
Authors: Outreville J. Francois 
Published: October 2018

PurposeNumerous articles contain recommendations as to how emerging countries can attract foreign direct investment on terms that are beneficial to both the investing firm and the host society but very few explore the conditions for firms from emerging countries to invest abroad. The purpose of this paper is twofold: the first is the documentation of the preferred locations of foreign affiliates for the largest financial groups headquartered in emerging countries; and, second, is to identify some of the determinants associated with the location-specific advantages of these host countries.Design/methodology/approachThe analysis of the internationalization process of these groups is based on a list of top financial groups ranked by total assets. In the empirical section, the factors that explain the choice of these locations by multinational firms are categorized as resources seeking, market seeking, efficiency-seeking variables and cultural variables.FindingsThere is empirical evidence that institutions prefer to invest in foreign locations that minimize some dimensions of the culture. Other factors like the role of efficiency variables, i.e. trade efficiency, political risk and government effectiveness, in host countries also have a strong impact on the determinants of the internationalization process.Originality/valueThe paper puts forward a framework for analyzing determinants of foreign direct investment of multinational financial groups from emerging economies.