bluuebunny/crossref_metadata_2025_split huggingface dataset:
Introduction: Methodologies for researching Africa
Authors: Bob-Milliar George M 
Published: April 2020

Abstract
This article ties the main issues raised in research notes that have been published by African Affairs. Research notes are dedicated to discussions of issues that arise in producing knowledge on Africa. These notes, drawn from rich experiences, tackle the above and other questions from various angles. The arguments and proposals presented are crucial for understanding the mutability of approaches and also raise important questions about how to sustain observed improvements and consolidate accrued gains towards a more fruitful, ethical, and fairer endeavour of studying Africa. These notes will inform and challenge academics in their thinking about issues ranging from methods and research design to negotiating their stakes in policy research partnerships. Africanists researchers will have to reflect deeply and selectively on what methodological approaches would best answer Africa’s peculiar problems. Africanists can engage in meaningful research when critique is deployed in selecting the methodology and possibly in getting the right research question. The insights from the notes might play a useful role on syllabi to help train and socialize the next generation of Africanists in the values of practical ethics and sustainable research engagements. Heterodox research methodologies will dominate the field of African studies for many years to come. And Africanists researchers should not allow their disciplinary or epistemic rules hold them back from using innovative methodologies to contribute to the intellectual output of the continent.
Driving in Parkinson’s disease: a retrospective study of driving and mobility assessments
Authors: Lloyd Katherine , Gaunt Daisy , Haunton Victoria , Skelly Rob , Mann Helen , Ben-Shlomo Yoav , Henderson Emily J 
Published: April 2020

Abstract

Background
To guide decision-making about driving ability, some patients with Parkinson’s disease (PD) undergo specialist driving assessment. However, decisions about driving safety in most patients need to be made without this definitive test. There is no consensus on what predicts unsafe driving in PD nor a validated prediction tool to guide clinician decision-making and the need to refer for further assessment.

Objectives
To describe the characteristics of patients with PD assessed at a Driving Mobility Centre and investigate factors that predict driving assessment outcome.

Methods
Retrospective cohort study of patients with PD assessed between 2012 and 2016. Descriptive analyses and logistic models to determine factors predicting a negative outcome.

Results
There were 86 assessments of patients with PD. The mean age was 70 years (±9.2), 86% were male, median disease duration 7 years (interquartile range 5–12.5 years) and 59% were referred by the Driver and Vehicle Licensing Agency. In total, 62% had a negative ‘not drive’ outcome. The Rookwood Driving Battery (RDB), depth of vision deficit, usual driving frequency, age, duration license held and response time were all predictors in univariable analysis. The RDB was the best predictor of assessment failure, conditional on other variables in a backward stepwise model (odds ratio 1.29; 95% confidence interval 1.05, 1.60; P = 0.015).

Conclusions
This is the first study to describe patients with PD undergoing driving assessments in the UK. In this population, RDB performance was the best predictor of outcome. Future prospective studies are required to better determine predictors of driving ability to guide development of prediction tools for implementation into clinical practice.
It’s not all about temperature: breeding success also affects nest design
Authors: Edwards Sophie C , Shoot Tanya T , Martin R Jeffrey , Sherry David F , Healy Susan D 
Published: April 2020

AbstractThere are numerous observational studies on intraspecific variation in avian nest building and a single experimental manipulation. The general consensus is that birds build nests in response to environmental conditions, but it is not clear whether such flexibility in nest building is reproductively advantageous. To test the relationship between building flexibility and reproductive success, we allowed captive zebra finches to build their first nest, using string, and to breed in temperature-controlled rooms held at 14 or 30 °C. Once the offspring had fledged, we returned half the pairs to breed at the same temperature while half the pairs were switched to the alternative temperature. We provided all pairs with string and left them to build and breed a second time. For their first nest, pairs that built at 14 °C used more string than did pairs that built at 30 °C, and pairs that bred successfully built a nest with more string than did unsuccessful pairs. When pairs built their second nest, however, temperature no longer explained the number of pieces of string they used; rather, irrespective of the ambient temperature, pairs that had successfully produced young from their first nest used the same amount of string for their second nest, whereas those that had failed to reproduce with their first nest used more string. These latter pairs were then more likely to reproduce successfully. Ambient temperature, therefore, did affect the nest the pairs built but only in the absence of reproductive experience.
Deep learning for biological age estimation
Authors: Ashiqur Rahman Syed , Giacobbi Peter , Pyles Lee , Mullett Charles , Doretto Gianfranco , Adjeroh Donald A 
Published: April 2020

Abstract
Modern machine learning techniques (such as deep learning) offer immense opportunities in the field of human biological aging research. Aging is a complex process, experienced by all living organisms. While traditional machine learning and data mining approaches are still popular in aging research, they typically need feature engineering or feature extraction for robust performance. Explicit feature engineering represents a major challenge, as it requires significant domain knowledge. The latest advances in deep learning provide a paradigm shift in eliciting meaningful knowledge from complex data without performing explicit feature engineering. In this article, we review the recent literature on applying deep learning in biological age estimation. We consider the current data modalities that have been used to study aging and the deep learning architectures that have been applied. We identify four broad classes of measures to quantify the performance of algorithms for biological age estimation and based on these evaluate the current approaches. The paper concludes with a brief discussion on possible future directions in biological aging research using deep learning. This study has significant potentials for improving our understanding of the health status of individuals, for instance, based on their physical activities, blood samples and body shapes. Thus, the results of the study could have implications in different health care settings, from palliative care to public health.
Synonymous variants in holoprosencephaly alter codon usage and impact the Sonic Hedgehog protein
Authors: Kim Artem , Le Douce Jérôme , Diab Farah , Ferovova Monika , Dubourg Christèle , Odent Sylvie , Dupé Valérie , David Véronique , Diambra Luis , Watrin Erwan , de Tayrac Marie 
Published: April 2020

Abstract
Synonymous single nucleotide variants (sSNVs) have been implicated in various genetic disorders through alterations of pre-mRNA splicing, mRNA structure and miRNA regulation. However, their impact on synonymous codon usage and protein translation remains to be elucidated in clinical context. Here, we explore the functional impact of sSNVs in the Sonic Hedgehog (SHH) gene, identified in patients affected by holoprosencephaly, a congenital brain defect resulting from incomplete forebrain cleavage. We identified eight sSNVs in SHH, selectively enriched in holoprosencephaly patients as compared to healthy individuals, and systematically assessed their effect at both transcriptional and translational levels using a series of in silico and in vitro approaches. Although no evidence of impact of these sSNVs on splicing, mRNA structure or miRNA regulation was found, five sSNVs introduced significant changes in codon usage and were predicted to impact protein translation. Cell assays demonstrated that these five sSNVs are associated with a significantly reduced amount of the resulting protein, ranging from 5% to 23%. Inhibition of the proteasome rescued the protein levels for four out of five sSNVs, confirming their impact on protein stability and folding. Remarkably, we found a significant correlation between experimental values of protein reduction and computational measures of codon usage, indicating the relevance of in silico models in predicting the impact of sSNVs on translation. Considering the critical role of SHH in brain development, our findings highlight the clinical relevance of sSNVs in holoprosencephaly and underline the importance of investigating their impact on translation in human pathologies.
Gray Matter Structure Is Associated with Reading Skill in Typically Developing Young Readers
Authors: Perdue Meaghan V , Mednick Joshua , Pugh Kenneth R , Landi Nicole 
Published: April 2020

Abstract
Research using functional and structural magnetic resonance imaging has identified areas of reduced brain activation and gray matter volume in children and adults with reading disability, but associations between cortical structure and individual differences in reading in typically developing children remain underexplored. Furthermore, the majority of research linking gray matter structure to reading ability quantifies gray matter in terms of volume, and cannot specify unique contributions of cortical surface area and thickness to these relationships. Here, we applied a continuous analytic approach to investigate associations between distinct surface-based properties of cortical structure and individual differences in reading-related skills in a sample of typically developing young children. Correlations between cortical structure and reading-related skills were conducted using a surface-based vertex-wise approach. Cortical thickness in the left superior temporal cortex was positively correlated with word and pseudoword reading performance. The observed positive correlation between cortical thickness in the left superior temporal cortex and reading may have implications for the patterns of brain activation that support reading.
Indirect effects of severe acute respiratory syndrome coronavirus 2 on the kidney in coronavirus disease patients
Authors: Couturier Aymeric , Ferlicot Sophie , Chevalier Kévin , Guillet Matthieu , Essig Marie , Jauréguiberry Stéphane , Collarino Rocco , Dargelos Mathilde , Michaut Alice , Geri Guillaume , Roque-Afonso Anne-Marie , Zaidan Mohamad , Massy Ziad A 
Published: April 2020

AbstractAmong patients hospitalized for novel coronavirus disease (COVID-19), between 10 and 14% develop an acute kidney injury and around half display marked proteinuria and haematuria. Post-mortem analyses of COVID-19 kidney tissue suggest that renal tubular cells and podocytes are affected. Here we report two cases of collapsing glomerulopathy and tubulointerstitial lesions in living COVID-19 patients. Despite our use of sensitive reverse transcription polymerase chain reaction techniques in this study, we failed to detect the virus in blood, urine and kidney tissues. Our observations suggest that these kidney lesions are probably not due to direct infection of the kidney by severe acute respiratory syndrome coronavirus 2.
Antitubercular Therapy Given to Differentiate Crohn’s Disease From Intestinal Tuberculosis Predisposes to Stricture Formation
Authors: Gupta Akshita , Pratap Mouli Venigalla , Mohta Srikant , Kante Bhaskar , Kalaivani Mani , Madhu Deepak , Sahu Pabitra , Kumar Sudheer , Sharma Raju , Sahni Peush , Das Prasenjit , Gupta Siddharth Datta , Makharia Govind , Kedia Saurabh , Ahuja Vineet 
Published: April 2020

Abstract

Background and Aim
Treatment trial with antitubercular therapy [ATT] is a common strategy in tuberculosis-endemic countries in case of a diagnostic dilemma between intestinal tuberculosis and Crohn’s disease [CD]. Our aim was to determine the long-term clinical course of patients who received ATT before an eventual diagnosis of CD was made.

Methods
We performed retrospective comparison between CD patients who received ≥6 months of ATT vs those who did not receive ATT. Outcomes assessed were change in disease behaviour during follow-up, requirement of surgery and medication use.

Results
In all, 760 patients with CD were screened for the study and, after propensity matching for location and behaviour of disease, 79 patients in each group were compared. Progression from inflammatory [B1] to stricturing/fistulising [B2/B3] phenotype was increased among CD patients who received ATT [B1, B2, B3: 73.4%, 26.6%, 0% at baseline vs: 41.8%, 51.9%, 6.3% at follow-up, respectively] as compared with those who did not receive ATT [B1, B2, B3: 73.4%, 26.6%, 0% at baseline vs: 72.2%, 27.8%, 0% at follow-up, respectively] with an odds ratio of 11.05[3.17–38.56]. The usage of 5-aminosalocylates, steroids, immunosuppressants and anti-tumour necrosis factor was similar between both the groups. On survival analysis, CD patients who received ATT had a lower probability of remaining free of surgery [45%] than those who did not [76%] at 14 years of follow-up (hazard ratio [HR] = 3.22, 95% confidence interval [CI], 1.46–7.12, p = 0.004].

Conclusions
Crohn’s disease patients diagnosed after a trial with antitubercular therapy had an unfavourable long-term disease course with higher rate of stricture formation and less chance of remaining free of surgery.
The Origins of the Interventionist State in France, 1830–1870
Authors: Greenfield Jerome 
Published: April 2020

Abstract
The historiography of the French state’s economic interventionism has focused primarily on the Ancien Régime and the period from the 1850s into the twentieth century. This article argues that, though often overlooked, the French state embarked on a major expansion in the 1830s and 1840s, as government spending on public works grew sharply. Most notably, the government contributed to the financing of railways and urban improvements. Following the 1848 revolution, rising pressure for fiscal rectitude forced a reconfiguration of the interventionist Orleanist state. While the new Bonapartist regime remained committed to public works, it relied more heavily on private finance than its predecessor, benefiting from the ‘great boom’ of the 1850s. Still, private enterprise remained inadequate to sustain public works without the support of public money, particularly once economic expansion began to slow in the 1860s. As a result, government spending on public works continued to rise under the Bonapartists. In this respect, they sustained the conception of an interventionist state developed by the Orleanists.
No antibiotic and toxic metabolites produced by the biocontrol agent Pseudomonas putida strain B2017
Authors: Daura-Pich Oriol , Hernández Iker , Pinyol-Escala Lola , Lara Jose M , Martínez-Servat Sonia , Fernández Carolina , López-García Belén 
Published: April 2020

ABSTRACT
Pseudomonas putida and closely-related species such as Pseudomonas fluorescens and Pseudomonas brassicacearum have been reported as potential biocontrol agents and plant growth-promoters. Recently, we have described the biocontrol activity of P. putida B2017 against several phytopathogens of agricultural relevance. In this study, its ability to produce potential antibiotic / toxic metabolites was assessed by functional, chromatography-mass spectrometry and genomic analysis. Our results show that B2017 is not able to synthesize surfactants and common antibiotics produced by Pseudomonas spp., i.e. pyrrolnitrin, 2,4-diacetylphloroglucinol, pyoluteorin and pyocyanin, but it produces pyoverdine, a siderophore which is involved in its biocontrol activity. The non-production of other metabolites, such as cyanide, safracin, promysalin and lipopeptides between others, is also discussed. Our data suggest that the mode of action of B2017 is not mainly due to the production of antimicrobial / toxic metabolites. Moreover, these features make P. putida B2017 a promising biocontrol microorganism for plant protection without side effects on environment, non-target organisms and human health.
Apolipoprotein ɛ4 Allele and Subjective Cognitive Functioning in Parents of Adults With Disabilities
Authors: Song Jieun , Mailick Marsha R , Greenberg Jan S 
Published: April 2020

Abstract

Objectives
Parents of individuals with disabilities face ongoing responsibilities of providing care and support for their children, even during the child’s adulthood. Past research has shown that this caregiving role is linked to chronic stress and subsequent adverse health outcomes for parents, including impaired cognition. This study examines the impacts of genetic risk for cognitive impairment (apolipoprotein [APOE] ɛ4 allele) among parents of adults with disabilities and comparison parents whose adult children do not have disabilities.

Method
We performed rank order regression analysis of data from the Wisconsin Longitudinal Study (2004–2006 and 2010–2012 surveys and DNA samples). Participants included parents of adults with disabilities (247 mothers and 159 fathers) and comparison parents whose adult children were not disabled (1,482 mothers and 954 fathers).

Results
Mothers who had adult children with disabilities and who were APOE ɛ4 carriers reported significantly declining levels of subjective cognitive functioning over time, but mothers of adults with disabilities who did not have the APOE ɛ4 allele did not manifest this change. Among comparison group mothers, cognitive change over time was not a function of their APOE ɛ4 carrier status. Fathers’ cognitive function did not differ significantly by either parental status or APOE ɛ4 carrier status.

Discussion
The results show that older mothers of adults with disabilities are more susceptible to cognitive impairment than their age peers if they have the genetic risk factor of APOE ɛ4 allele.
Robust well-log based determination of rock thermal conductivity through machine learning
Authors: Meshalkin Yury , Shakirov Anuar , Popov Evgeniy , Koroteev Dmitry , Gurbatova Irina 
Published: April 2020

SUMMARYRock thermal conductivity is an essential input parameter for enhanced oil recovery methods design and optimization and for basin and petroleum system modelling. Absence of any effective technique for direct in situ measurements of rock thermal conductivity makes the development of well-log based methods for rock thermal conductivity determination highly desirable. A major part of the existing problem solutions is regression model-based approaches. Literature review revealed that there are only several studies performed to assess the applicability of neural network-based algorithms to predict rock thermal conductivity from well-logging data. In this research, we aim to define the most effective machine-learning algorithms for well-log based determination of rock thermal conductivity. Well-logging data acquired at a heavy oil reservoir together with results of thermal logging on cores extracted from two wells were the basis for our research. Eight different regression models were developed and tested to predict vertical variations of rock conductivity from well-logging data. Additionally, rock thermal conductivity was determined based on Lichtenecker–Asaad model. Comparison study of regression-based and theoretical-based approaches was performed. Among considered machine learning techniques Random Forest algorithm was found to be the most accurate at well-log based determination of rock thermal conductivity. From a comparison of the thermal conductivity—depth profile predicted from well-logging data with the experimental data, and it can be concluded that thermal conductivity can be determined with a total relative error of 12.54 per cent. The obtained results prove that rock thermal conductivity can be inferred from well-logging data for wells that are drilled in a similar geological setting based on the Random Forest algorithm with an accuracy sufficient for industrial needs.
Wave-equation dispersion spectrum inversion for near-surface characterization using fibre-optics acquisition
Authors: Zhang Zhen-dong , Alajami Mamdoh , Alkhalifah Tariq 
Published: April 2020

SUMMARY
Distributed acoustic sensing (DAS) acquisition is becoming more and more popular for its dense sampling at a lower cost than seismometers. However, data processing for DAS data is challenging, especially for surface-deployedfibers, in which only the horizontal component of strain variation is effectively recorded. Also, the coupling between the fiber and the Earth is usually poor and the recorded single-component data are noisy. Thus, we introduce data processing strategies dedicated to enhancing the ambient-noise and active-source seismic data recorded by a horizontally deployed tactical fiber-optics cable buried in a sand dune area in Saudi Arabia. We propose a similarity-weighted stacking of randomly selected short-time duration windows to generate virtual common shot gathers (CSG) from the recorded ambient noise. The similarity-weighted stacking only counts the primary contributions of coherent events, while a short-time correlation can suppress the crosstalk usually present in late arrivals. The stacking fold is preserved or even can be increased by generating plenty of random time segments compared to stacking the full recording time. For the recorded active-source data, we skip the interferometric step, but use the envelope of the CSG. The envelope is needed to mitigate the complexity of waveforms, while preserving the slopes of arrivals. Then, we use the wave-equation-based Rayleigh-wave dispersion spectrum inversion, which utilizes all the dispersion modes available and does not require picking the dispersion curve, in estimating the shallow S-wave velocities. The local cross-correlation objective function allows for additional freedom in matching the modelled and observed data, and thus, helps us avoid falling into a local minimum when starting with kinematically poor velocity models.
Randomized sketch descent methods for non-separable linearly constrained optimization
Authors: Necoara Ion , Takáč Martin 
Published: April 2020

Abstract
In this paper we consider large-scale smooth optimization problems with multiple linear coupled constraints. Due to the non-separability of the constraints, arbitrary random sketching would not be guaranteed to work. Thus, we first investigate necessary and sufficient conditions for the sketch sampling to have well-defined algorithms. Based on these sampling conditions we develop new sketch descent methods for solving general smooth linearly constrained problems, in particular, random sketch descent (RSD) and accelerated random sketch descent (A-RSD) methods. To our knowledge, this is the first convergence analysis of RSD algorithms for optimization problems with multiple non-separable linear constraints. For the general case, when the objective function is smooth and non-convex, we prove for the non-accelerated variant sublinear rate in expectation for an appropriate optimality measure. In the smooth convex case, we derive for both algorithms, non-accelerated and A-RSD, sublinear convergence rates in the expected values of the objective function. Additionally, if the objective function satisfies a strong convexity type condition, both algorithms converge linearly in expectation. In special cases, where complexity bounds are known for some particular sketching algorithms, such as coordinate descent methods for optimization problems with a single linear coupled constraint, our theory recovers the best known bounds. Finally, we present several numerical examples to illustrate the performances of our new algorithms.