bluuebunny/crossref_metadata_2025_split huggingface dataset:
Demonstrating the influence of HTA: INAHTA member stories of HTA impact
Authors: Werkö Sophie Söderholm , Merlin Tracy , Lambert Laurie Jean , Fennessy Paul , Galán Ana Pérez , Schuller Tara 
Published: November 2020

AbstractA central function of health technology assessment (HTA) agencies is the production of HTA reports to support evidence-informed policy and decision making. HTA agencies are interested in understanding the mechanisms of HTA impact, which can be understood as the influence or impact of HTA report findings on decision making at various levels of the health system. The members of the International Network of Agencies for HTA (INAHTA) meet at their annual Congress where impact story sharing is one important activity. This paper summarizes four stories of HTA impact that were finalists for theDavid Hailey Award for Best Impact Story.The methods to measure impact include: document review; claims analysis and review of reimbursement status; citation analysis; qualitative evaluation of stakeholders’ views; and review of media response. HTA agency staff also observed changes in government activities and priorities based on the HTA. Impact assessment can provide information to improve the HTA process, for example, the value of patient and clinician engagement in the HTA process to better define the assessment question and literature reviews in a more holistic and balanced way.HTA reports produced by publicly funded HTA agencies are valued by health systems around the globe as they support decision making regarding the appropriate use, pricing, reimbursement, and disinvestment of health technologies. HTAs can also have a positive impact on information sharing between different levels of government and across stakeholder groups. These stories show how HTA can have a significant impact, irrespective of the health system and health technology being assessed.
Evaluating aircraft cockpit emotion through a neural network approach
Authors: Chen Yanhao , Yu Suihuai , Chu Jianjie , Chen Dengkai , Yu Mingjiu 
Published: November 2020

AbstractStudies show that there are shortcomings in applying conventional methods for the emotional evaluation of the aircraft cockpit. In order to resolve this problem, a more efficient cockpit emotion evaluation system is established in the present study to simply and quickly obtain the cockpit emotion evaluation value. To this end, the neural network is applied to construct an emotional model to evaluate the emotional prediction of the interior design of the aircraft cockpit. Moreover, several technologies and the Kansei engineering method are applied to acquire the cockpit interior emotional evaluation data for typical aircraft models. In this regard, the radical basis function neural network (RBFNN), Elman neural network (ENN), and the general regression neural network (GRNN) are applied to construct the sentimental prediction evaluation model. Then, the three models are comprehensively compared through factors such as the model evaluation criteria, network structure, and network parameters. Obtained experimental results indicate that the GRNN not only has the highest classification accuracy but also has the highest stability in comparison to the other two neural networks, so that it is a more appropriate method for the emotional evaluation of the aircraft cockpit. Results of the present study provide decision supports for the emotional evaluation of the cockpit interior space.
Rapid response of a cardiac rhabdomyoma causing severe right ventricular outflow obstruction to Sirolimus in an infant with negative genetics for Tuberous sclerosis
Authors: Nir-David Yifat , Brosilow Sharon , Khoury Asaad 
Published: November 2020

AbstractMammalian target of rapamycin inhibitors was found recently to be an effective treatment for manifestations of Tuberous sclerosis complex, including cardiac rhabdomyomas. Most cases with Cardiac rhabdomyoma treated with mammalian target of rapamycin inhibitors to date were diagnosed with Tuberous sclerosis. We report a case of cardiac rhabdomyoma and severe right ventricular outflow obstruction in a baby with negative genetics for Tuberous sclerosis that responded rapidly to Sirolimus.
The deforestation-income relationship: evidence of deforestation convergence across developing countries
Authors: Assa Boka Stéphane Kévin 
Published: November 2020

AbstractThe importance of forest conservation in the fight against emissions from deforestation and forest degradation has led to reexamination of the deforestation and economic development relationship. For this purpose, we use the recent method of long-term growth rate developed by Stern et al. (2017) on 85 tropical developing countries over the period 1990–2010. Results show that the EKC is not significant. However, we find a beta convergence across developing countries in terms of deforestation per capita. In other words, these countries converge in terms of policies that prevent deforestation and forest degradation. This implies that, just as with growth effects, beta convergence effects are also important in explaining changes in forest cover in tropical developing countries. The convergence effect in forest cover change may be consistent with the forest transition hypothesis.
Francis Hutcheson on Liberty
Authors: Boeker Ruth 
Published: November 2020

AbstractThis paper aims to reconstruct Francis Hutcheson's thinking about liberty. Since he does not offer a detailed treatment of philosophical questions concerning liberty in his mature philosophical writings I turn to a textbook on metaphysics. We can assume that he prepared the textbook during the 1720s in Dublin. This textbook deserves more attention. First, it sheds light on Hutcheson's role as a teacher in Ireland and Scotland. Second, Hutcheson's contributions to metaphysical disputes are more original than sometimes assumed. To appreciate his independent thinking, I argue, it is helpful to take the intellectual debates in Ireland into consideration, including William King's defence of free will and discussions of Shaftesbury's views in Robert Molesworth's intellectual circle. Rather than taking a stance on the philosophical disputes about liberty, I argue that Hutcheson aims to shift the focus of the debates towards practical questions concerning control of desire, cultivation of habits, and character development.
‘Plainly of Considerable Moment in Human Society’: Francis Hutcheson and Polite Laughter in Eighteenth-Century Britain and Ireland
Authors: Davison Kate 
Published: November 2020

AbstractThis article focuses on Francis Hutcheson'sReflections Upon Laughter, which was originally published in 1725 as a series of three letters toThe Dublin Journalduring his time in the city. Although rarely considered a significant example of Hutcheson's published work,Reflections Upon Laughterhas long been recognised in the philosophy of laughter as a foundational contribution to the ‘incongruity theory’ – one of the ‘big three’ theories of laughter, and that which is still considered the most credible by modern theorists. The article gives an account of Hutcheson's text but, rather than evaluating it solely as an explanation of laughter, the approach taken is an historical one: it emphasises the need to reconnect the theory to the cultural and intellectual contexts in which it was published and to identify the significance of Hutcheson's arguments in time and place. Through this, the article argues that Hutcheson's theory of laughter is indicative of the perceived significance of human risibility in early eighteenth-century Britain and Ireland and, more broadly, that it contributed both to moral philosophical debate and polite conduct guidance.
What the Women of Dublin Did with John Locke
Authors: Gerrard Christine 
Published: November 2020

AbstractWilliam Molyneux's friendship with John Locke helped make Locke's ideas well known in early eighteenth-century Dublin. TheEssay Concerning Human Understandingwas placed on the curriculum of Trinity College in 1692, soon after its publication. Yet there has been very little discussion of whether Irish women from this period read or knew Locke's work, or engaged more generally in contemporary philosophical debate. This essay focuses on the work of Laetitia Pilkington (1709–1750) and Mary Barber (1685–1755), two of the Dublin women writers of the so-called ‘Triumfeminate’, a literary and intellectual circle connected to Jonathan Swift which met and discussed ideas at the home of Patrick Delaney. Pilkington and Barber were particularly influenced by Locke's ideas on obstetrics and childhood in hisSome Thoughts Concerning Educationand especially by his discussion of memory in theEssay Concerning Human Understanding. Both authors engage playfully and imaginatively with Locke's theories, especially in a domestic context. Not all philosophical debates took place in the public male spaces of school, coffee house and university. This essay attempts to recreate the contexts in which intellectually curious women of the ‘middling sort’ encountered and engaged with philosophical ideas, especially those of Locke, and how these shaped their writing.
From Serena to Hypatia: John Toland's Women
Authors: Leask Ian 
Published: November 2020

AbstractThis paper focusses on John Toland's influentialHypatia(1720), an account of the neo-Platonist philosopher and mathematician murdered in ancient Alexandria; it also considers segments of hisLetters to Serena(1704), and suggests various conjunctions between the two texts which confirm Toland's genuine and sustained feminist commitment. As I try to establish, Toland's concern is as much about contemporaneous events as it is about ‘disinterested’ history: by promoting Hypatia as the representative of philosophy in its perennial struggle with superstition and priestcraft, Toland is able to underscore the wider case for an inclusive and capacious conception of ‘enlightenment’.
Spanish Adaptation and Psychometric Properties of the Parent Version of the Short Mood and Feelings Questionnaire (SMFQ-P) in a Non-Clinical Sample of Young School-Aged Children
Authors: Fernández-Martínez Iván , Morales Alexandra , Méndez Francisco Xavier , Espada José Pedro , Orgilés Mireia 
Published: November 2020

Abstract
The parent version of the Short Mood and Feelings Questionnaire (SMFQ-P) is a brief 13-item tool for the screening of depression in children from the age of 6 years. Despite the wide use of the SMFQ-P, its psychometric properties and factor structure remain understudied, with few data available for young school-aged children. The objective of this study was to examine for the first time the factorial structure and psychometric properties of the SMFQ-P in a non-clinical sample of Spanish-speaking children aged 6–8 years. Participants were 181 children whose parents completed the Spanish-adapted version of the SMFQ-P along with the parent version of other measures of anxiety and general difficulties and positive attributes. The SMFQ-P demonstrated adequate internal consistency (α = .83) and test-retest reliability over an eight-week period (ICC = .80), and good convergent and divergent validity. Factor analysis confirmed the original 13-item model, thus supporting the unidimensionality of the measure in the Spanish sample. Overall, this study provides initial empirical evidence for the utility of the SMFQ-P with Spanish-speaking children from early school ages, and extends the international support of the measure.
Future Risks of Unprecedented Compound Heat Waves Over Three Vast Urban Agglomerations in China
Authors: Wang Jun , Feng Jinming , Yan Zhongwei , Chen Yang 
Published: November 2020

Key Points

Unprecedented compound heat waves will occur on a regular basis in three urban agglomerations in China since mid‐21st century under RCP8.5
The likelihood of unprecedented compound heat waves in a 1.5°C warmer world will halve compared to 2°C warming scenario
Population exposures to future unprecedented compound heat waves will increase by nearly 70, 90, and 60 million by the end of this century
Brine Migration and Impact‐Induced Cryovolcanism on Europa
Authors: Steinbrügge G. , Voigt J. R. C. , Wolfenbarger N. S. , Hamilton C. W. , Soderlund K. M. , Young D. A. , Blankenship D. D. , Vance S. D. , Schroeder D. M. 
Published: November 2020

AbstractDespite evidence for plumes on Jupiter's moon Europa, no surface features have been definitively identified as the source of the plumes to date. Furthermore, it remains unknown whether the activity originates from near‐surface water reservoirs within the ice shell or if it is sourced from the underlying global ocean. Here we investigate brine pocket migration, studied previously in the context of sea ice on Earth, as a process for transporting brine along thermal gradients. We show that the fracture system located in the center of Europa's Manannán crater is consistent with the formation of a subsurface brine reservoir. After the initial impact, residual aqueous melt concentrated via brine pocket migration as the target material cooled. Freezing and overpressurization then resulted in a cryovolcanic eruption. The volume of the emptied reservoir and the critical composition at the end of migration provide further constraints on the average salinity of Europa's ice shell.
Wave Generation Across a Continuum of Landslide Conditions From the Collapse of Partially Submerged to Fully Submerged Granular Columns
Authors: Cabrera Miguel A. , Pinzon Gustavo , Take W. Andy , Mulligan Ryan P. 
Published: November 2020

AbstractLandslide generated tsunamis are a primary natural hazard to coastal communities and infrastructure, but the present state of knowledge is limited to the specific details of momentum transfer from the landslide to the water body for either subaerial or fully submerged conditions. Here we report a series of novel experiments and an analytical model that bridges this gap, by exploring the collapse of a granular column for a wide range of water depths. We show that the maximum seaward wave amplitude is governed by a single dimensionless ratio, the relative depth of submergence. Based on the experimental observations, we propose a continuous function that quantifies the maximum wave amplitude by considering the momentum flux from the initially vertical granular column to the initially still fluid. Predictions made using the momentum function are in good agreement with observations of the present study and with other experimental studies of granular column collapse at larger scales. The analytical model allows the prediction of maximum wave amplitude over the full range of submergence conditions from subaerial to partially submerged and fully submerged collapses, with potential applications for tsunami hazard assessment.
Effect of Cold Front‐Induced Waves Along Wetlands Boundaries
Authors: Kim Jin‐Young , Kaihatu James , Chang Kuang‐An , Sun Shih‐Heng , Huff Thomas P. , Feagin Rusty A. 
Published: November 2020

AbstractAlong wetland shorelines, the energetic wave environment generated by cold fronts occurs more frequently than for major storms, yet their impact on wetland evolution processes has not been fully identified. To capture the changes in wave climate during the passage of cold fronts, a wave gauge was installed near a salt marsh edge in Galveston Bay, Texas, USA. A coupled wave‐hydrodynamic model, validated with the data, was used to assess the dominant processes of cold front induced surge and waves. During the measurement period, wind gusts and abrupt direction shifts during cold fronts produced high‐energy wave events that propagated toward the wetland edge. Before a cold front passed our study area, there was an initial increase in the water level inside the bay. As soon as the cold front passed and the wind direction shifted, large waves were created by strong winds. Over the first few hours, the relatively high water level reduced the depth limitations on these waves, allowing them to be quite large. However, as the waves struck the wetland edge at these higher water levels, vegetation intercepted and dampened the erosive force. Over the next few days, the water level dropped well below the mean tide, allowing plunging waves to impinge directly on the edge with a high‐energy flux. From the calculated wave power during the entire measurement period, it was found that cold front‐induced waves, despite their brief duration, had a high erosive impact on the evolution of the wetland edge.
A Probabilistic Approach to Determination of Ceres' Average Surface Composition From Dawn Visible‐Infrared Mapping Spectrometer and Gamma Ray and Neutron Detector Data
Authors: Kurokawa H. , Ehlmann B. L. , De Sanctis M. C. , Lapôtre M. G. A. , Usui T. , Stein N. T. , Prettyman T. H. , Raponi A. , Ciarniello M. 
Published: November 2020

AbstractThe Visible‐Infrared Mapping Spectrometer (VIR) on board the Dawn spacecraft revealed that aqueous secondary minerals—Mg‐phyllosilicates, NH4‐bearing phases, and Mg/Ca carbonates—are ubiquitous on Ceres. Ceres' low reflectance requires dark phases, which were assumed to be amorphous carbon and/or magnetite (∼80 wt.%). In contrast, the Gamma Ray and Neutron Detector (GRaND) constrained the abundances of C (8–14 wt.%) and Fe (15–17 wt.%). Here, we reconcile the VIR‐derived mineral composition with the GRaND‐derived elemental composition. First, we model mineral abundances from VIR data, including either meteorite‐derived insoluble organic matter (IOM), amorphous carbon, magnetite, or combination as the darkening agent and provide statistically rigorous error bars from a Bayesian algorithm combined with a radiative‐transfer model. Elemental abundances of C and Fe are much higher than is suggested by the GRaND observations for all models satisfying VIR data. We then show that radiative transfer modeling predicts higher reflectance from a carbonaceous chondrite of known composition than its measured reflectance. Consequently, our second models use multiple carbonaceous chondrite endmembers, allowing for the possibility that their specific textures or minerals other than carbon or magnetite act as darkening agents, including sulfides and tochilinite. Unmixing models with carbonaceous chondrites eliminate the discrepancy in elemental abundances of C and Fe. Ceres' average reflectance spectrum and elemental abundances are best reproduced by carbonaceous‐chondrite‐like materials (40–70 wt.%), IOM or amorphous carbon (10 wt.%), magnetite (3–8 wt.%), serpentine (10–25 wt.%), carbonates (4–12 wt.%), and NH4‐bearing phyllosilicates (1–11 wt.%).
GDC-0349 inhibits non-small cell lung cancer cell growth
Authors: Yang Han , Zhao Jun , Zhao Mengjing , Zhao Lihao , Zhou Li-na , Duan Yuxia , Li Gang 
Published: November 2020

AbstractNon-small cell lung cancer (NSCLC) is a leading cause of cancer-related human mortality with a clear need for new therapeutic intervention. GDC-0349 is a potent and selective ATP-competitive mTOR inhibitor. In A549 cells and primary human NSCLC cells, GDC-0349 inhibited cell growth, proliferation, cell cycle progression, migration and invasion, while inducing significant apoptosis activation. Although GDC-0349 blocked Akt-mTORC1/2 activation in NSCLC cells, it also exerted cytotoxicity in Akt1-knockout A549 cells. Furthermore, restoring Akt-mTOR activation by a constitutively-active Akt1 only partially attenuated GDC-0349-induced A549 cell apoptosis, indicating the existence of Akt-mTOR-independent mechanisms. In NSCLC cells GDC-0349 induced sphingosine kinase 1 (SphK1) inhibition, ceramide accumulation, JNK activation and oxidative injury. Conversely, N-acetylcysteine, the JNK inhibitor and sphingosine 1-phosphate alleviated GDC-0349-induced NSCLC cell apoptosis. In vivo, daily oral administration of GDC-0349 potently inhibited NSCLC xenograft growth in mice. Akt-mTOR in-activation, SphK1 inhibition, JNK activation and oxidative stress were detected in NSCLC xenograft tissues with GDC-0349 administration. In summary, GDC-0349 inhibits NSCLC cell growth via Akt-mTOR-dependent and Akt-mTOR-independent mechanisms.
Engineering microrobots for targeted cancer therapies from a medical perspective
Authors: Schmidt Christine K. , Medina-Sánchez Mariana , Edmondson Richard J. , Schmidt Oliver G. 
Published: November 2020

AbstractSystemic chemotherapy remains the backbone of many cancer treatments. Due to its untargeted nature and the severe side effects it can cause, numerous nanomedicine approaches have been developed to overcome these issues. However, targeted delivery of therapeutics remains challenging. Engineering microrobots is increasingly receiving attention in this regard. Their functionalities, particularly their motility, allow microrobots to penetrate tissues and reach cancers more efficiently. Here, we highlight how different microrobots, ranging from tailor-made motile bacteria and tiny bubble-propelled microengines to hybrid spermbots, can be engineered to integrate sophisticated features optimised for precision-targeting of a wide range of cancers. Towards this, we highlight the importance of integrating clinicians, the public and cancer patients early on in the development of these novel technologies.
Cumulative learning enables convolutional neural network representations for small mass spectrometry data classification
Authors: Seddiki Khawla , Saudemont Philippe , Precioso Frédéric , Ogrinc Nina , Wisztorski Maxence , Salzet Michel , Fournier Isabelle , Droit Arnaud 
Published: November 2020

AbstractRapid and accurate clinical diagnosis remains challenging. A component of diagnosis tool development is the design of effective classification models with Mass spectrometry (MS) data. Some Machine Learning approaches have been investigated but these models require time-consuming preprocessing steps to remove artifacts, making them unsuitable for rapid analysis. Convolutional Neural Networks (CNNs) have been found to perform well under such circumstances since they can learn representations from raw data. However, their effectiveness decreases when the number of available training samples is small, which is a common situation in medicine. In this work, we investigate transfer learning on 1D-CNNs, then we develop a cumulative learning method when transfer learning is not powerful enough. We propose to train the same model through several classification tasks over various small datasets to accumulate knowledge in the resulting representation. By using rat brain as the initial training dataset, a cumulative learning approach can have a classification accuracy exceeding 98% for 1D clinical MS-data. We show the use of cumulative learning using datasets generated in different biological contexts, on different organisms, and acquired by different instruments. Here we show a promising strategy for improving MS data classification accuracy when only small numbers of samples are available.