bluuebunny/crossref_metadata_2025_split huggingface dataset:
Surgery triage during the COVID‐19 pandemic
Authors: Babidge Wendy J. , Tivey David R. , Kovoor Joshua G. , Weidenbach Kristin , Collinson Trevor G. , Hewett Peter J. , Hugh Thomas J. , Padbury Robert T. A. , Hill Nicola M. , Maddern Guy J. 
Published: July 2020

AbstractBackgroundThe novel coronavirus, SARS‐CoV‐2, caused the COVID‐19 global pandemic. In response, the Australian and New Zealand governments activated their respective emergency plans and hospital frameworks to deal with the potential increased demand on scarce resources. Surgical triage formed an important part of this response to protect the healthcare system's capacity to respond to COVID‐19.MethodA rapid review methodology was adapted to search for all levels of evidence on triaging surgery during the current COVID‐19 outbreak. Searches were limited to PubMed (inception to 10 April 2020) and supplemented with grey literature searches using the Google search engine. Further, relevant articles were also sourced through the Royal Australasian College of Surgeons COVID‐19 Working Group. Recent government advice (May 2020) is also included.ResultsThis rapid review is a summary of advice from Australian, New Zealand and international speciality groups regarding triaging of surgical cases, as well as the peer‐reviewed literature. The key theme across all jurisdictions was to not compromise clinical judgement and to enable individualized, ethical and patient‐centred care. The topics reported on include implications of COVID‐19 on surgical triage, competing demands on healthcare resources (surgery versus COVID‐19 cases), and the low incidence of COVID‐19 resulting in a possibility to increase surgical caseloads over time.ConclusionDuring the COVID‐19 pandemic, urgent and emergency surgery must continue. A carefully staged return of elective surgery should align with a decrease in COVID‐19 caseload. Combining evidence and expert opinion, schemas and recommendations have been proposed to guide this process in Australia and New Zealand.
Philanthropic zakat for the disadvantaged: Recipient perspectives from Indonesia
Authors: Lessy Zulkipli , Adamek Margaret , Khaja Khadija 
Published: July 2020

AbstractRumah Zakat, a charitable institution, is a proactive provider of charity, enabling sustainable progress in the lives of needy recipients. This study focused on three forms of philanthropic zakat assistance: economic empowerment, health care, and tuition‐free education. There were 21 participants—seven from each respective cluster. Interviewers were employed to elicit participants’ perspectives. Major findings showed economic empowerment recipients were the poor affected by the earthquake and the monetary crisis. Zakat helped them re‐open their businesses. As they grew, most felt satisfied and employed jobless individuals. Recipients of health care with elementary education had a five‐year grant of free health care and health education. Although the service lowered their expenses, some needed extra help with food. Participants benefitting from either program reported positive impacts on their income, health, and social lives. Most participants in the tuition‐free education were satisfied with their children's schooling, the extracurricular options, and the chances for parental involvement in the social engagement. Some stated the charitable schools emphasized moral education over science; thus, they were concerned about sufficient preparation for future competitive educational levels. Recipients would benefit from the charities if three programs were altogether offered. This study suggests the integrative community development programs should be reviewed for better services.
All in the Mind: Citizen Satisfaction and Financial Performance in the Victorian Local Government System
Authors: Tran Carolyn‐Dung Thi Thanh , Dollery Brian 
Published: July 2020

AbstractWhile a significant body of literature exists on local government efficiency, much less is known about its effectiveness, especially financial performance and resident satisfaction. To address this gap in the empirical literature, the present paper uses system‐wide official annual data on resident satisfaction in the Victorian state local government system in Australia to investigate the relationship between annual net operating results and overall citizen satisfaction. In addition, in order to garner a deeper understanding of this relationship, we evaluated the assumption in the ‘near‐to‐zero balance’ public accounting literature that local residents prefer an insignificant annual balance in operating performance compared to substantial annual losses or surpluses. We found that there is a significant negative association between overall satisfaction and its components and financial performance for Victorian local government as a whole. However, this association is largely restricted to rural councils with surpluses. By contrast, we find no relationship between satisfaction and near‐to‐zero balances. We conclude by considering the implications of our findings for both the public accounting literature and local government policymaking.
A Bayesian multivariate mixture model for skewed longitudinal data with intermittent missing observations: An application to infant motor development
Authors: Allen Carter , Benjamin‐Neelon Sara E. , Neelon Brian 
Published: July 2020

AbstractIn studies of infant growth, an important research goal is to identify latent clusters of infants with delayed motor development—a risk factor for adverse outcomes later in life. However, there are numerous statistical challenges in modeling motor development: the data are typically skewed, exhibit intermittent missingness, and are correlated across repeated measurements over time. Using data from the Nurture study, a cohort of approximately 600 mother‐infant pairs, we develop a flexible Bayesian mixture model for the analysis of infant motor development. First, we model developmental trajectories using matrix skew‐normal distributions with cluster‐specific parameters to accommodate dependence and skewness in the data. Second, we model the cluster‐membership probabilities using a Pólya‐Gamma data‐augmentation scheme, which improves predictions of the cluster‐membership allocations. Lastly, we impute missing responses from conditional multivariate skew‐normal distributions. Bayesian inference is achieved through straightforward Gibbs sampling. Through simulation studies, we show that the proposed model yields improved inferences over models that ignore skewness or adopt conventional imputation methods. We applied the model to the Nurture data and identified two distinct developmental clusters, as well as detrimental effects of food insecurity on motor development. These findings can aid investigators in targeting interventions during this critical early‐life developmental window.
Analysis of noisy survival data with graphical proportional hazards measurement error models
Authors: Chen Li‐Pang , Yi Grace Y. 
Published: July 2020

AbstractIn survival data analysis, the Cox proportional hazards (PH) model is perhaps the most widely used model to feature the dependence of survival times on covariates. While many inference methods have been developed under such a model or its variants, those models are not adequate for handling data with complex structured covariates. High‐dimensional survival data often entail several features: (1) many covariates are inactive in explaining the survival information, (2) active covariates are associated in a network structure, and (3) some covariates are error‐contaminated. To hand such kinds of survival data, we propose graphical PH measurement error models and develop inferential procedures for the parameters of interest. Our proposed models significantly enlarge the scope of the usual Cox PH model and have great flexibility in characterizing survival data. Theoretical results are established to justify the proposed methods. Numerical studies are conducted to assess the performance of the proposed methods.
Segmentation’s failure to improve software video tutorials
Authors: Garrett Nathan 
Published: July 2020

AbstractSegmentation reduces learners’ cognitive load by inserting system‐controlled pauses into instructional animations and video. However, many previous studies focus on conceptual knowledge, and do not allow users control over the pacing of instruction. This two‐part experiment attempted to validate segmentation in the context of procedural software instruction by applying it to an Excel conditional formatting tutorial. Learners assigned to segmented video failed to show either improved knowledge transfer or decreased cognitive load. Instead, learners using the videos were able to successfully use the pause and rewind features to manage their own cognitive load. This study shows the importance of providing users with control over the pacing of instruction, and with testing educational theories when applying them in a new context.
Intracellular levels of reactive oxygen species correlate with ABT‐263 sensitivity in non‐small‐cell lung cancer cells
Authors: Ohgino Keiko , Terai Hideki , Yasuda Hiroyuki , Nukaga Shigenari , Hamamoto Junko , Tani Tetsuo , Kuroda Aoi , Arai Daisuke , Ishioka Kota , Masuzawa Keita , Ikemura Shinnosuke , Kawada Ichiro , Naoki Katsuhiko , Fukunaga Koichi , Soejima Kenzo 
Published: July 2020

AbstractABT‐263 (Navitoclax) is a BH3‐mimetic drugs targeting anti‐apoptotic B‐cell lymphoma‐2 (BCL‐2) family proteins, including BCL‐2, BCL‐xL, and BCL‐w, thereby inducing apoptosis. In small‐cell lung cancer (SCLC) cells, the response to ABT‐263 is associated with the expression of myeloid cell leukemia‐1 (MCL‐1) protein, however the efficacy of ABT‐263 in non‐small‐cell lung cancer (NSCLC) has not been thoroughly evaluated. There are currently no established biomarkers for predicting the efficacy of ABT‐263 treatment in NSCLC. We screened a panel of different NSCLC cell lines and found that ABT‐263 inhibited cell proliferation and induced apoptosis in Calu‐1, Calu‐3, and BID007 cells. Inconsistent with previous reports on SCLC, low levels of MCL‐1 did not predict the response to ABT‐263 in NSCLC cells, however we found that intracellular levels of reactive oxygen species (ROS) in cancer cells were associated with sensitivity to ABT‐263 in NSCLC cells. We also showed that increasing the level of intracellular ROS could enhance the sensitivity to ABT‐263 in NSCLC cells. In summary, we propose that the intracellular levels of ROS could be used as a potential novel biomarker for predicting a response to ABT‐263 in NSCLC. Furthermore, we show some evidence supporting the further assessment of ABT‐263 as a new therapeutic strategy in patients with NSCLC combined with agents regulating ROS levels. We believe that our findings and follow‐up studies on this matter would lead to novel diagnostic and treatment strategies in patients with NSCLC.
A review of the tumour spectrum of germline succinate dehydrogenase gene mutations: Beyond phaeochromocytoma and paraganglioma
Authors: MacFarlane James , Seong Keat Cheah , Bisambar Chad , Madhu Basetti , Allinson Kieren , Marker Alison , Warren Anne , Park Soo‐Mi , Giger Olivier , Challis Benjamin G. , Maher Eamonn R. , Casey Ruth T. 
Published: July 2020

AbstractThe citric acid cycle, also known as the Krebs cycle, plays an integral role in cellular metabolism and aerobic respiration. Mutations in genes encoding the citric acid cycle enzymes succinate dehydrogenase, fumarate hydratase and malate dehydrogenase all predispose to hereditary tumour syndromes. The succinate dehydrogenase enzyme complex (SDH) couples the oxidation of succinate to fumarate in the citric acid cycle and the reduction of ubiquinone to ubiquinol in the electron transport chain. A loss of function in the succinate dehydrogenase (SDH) enzyme complex is most commonly caused by an inherited mutation in one of the fourSDHxgenes (SDHA,SDHB,SDHCandSDHD). This mechanism was first implicated in familial phaeochromocytoma and paraganglioma. However, over the past two decades the spectrum of tumours associated with SDH deficiency has been extended to include gastrointestinal stromal tumours (GIST), renal cell carcinoma (RCC) and pituitary adenomas. The aim of this review is to describe the extended tumour spectrum associated withSDHxgene mutations and to consider how functional tests may help to establish the role ofSDHxmutations in new or unexpected tumour phenotypes.
A Scalable and Production Ready Sky and Atmosphere Rendering Technique
Authors: Hillaire Sébastien 
Published: July 2020

AbstractWe present a physically based method to render the atmosphere of a planet from ground to space views. Our method is cheap to compute and, as compared to previous successful methods, does not require any high dimensional Lookup Tables (LUTs) and thus does not suffer from visual artifacts associated with them. We also propose a new approximation to evaluate light multiple scattering within the atmosphere in real time. We take a new look at what it means to render natural atmospheric effects, and propose a set of simple look up tables and parameterizations to render a sky and its aerial perspective. The atmosphere composition can change dynamically to match artistic visions and weather changes without requiring heavy LUT update. The complete technique can be used in real‐time applications such as games, simulators or architecture pre‐visualizations. The technique also scales from power‐efficient mobile platforms up to PCs with high‐end GPUs, and is also useful for accelerating path tracing.
Deep Kernel Density Estimation for Photon Mapping
Authors: Zhu Shilin , Xu Zexiang , Jensen Henrik Wann , Su Hao , Ramamoorthi Ravi 
Published: July 2020

AbstractRecently, deep learning‐based denoising approaches have led to dramatic improvements in low sample‐count Monte Carlo rendering. These approaches are aimed at path tracing, which is not ideal for simulating challenging light transport effects like caustics, where photon mapping is the method of choice. However, photon mapping requires very large numbers of traced photons to achieve high‐quality reconstructions. In this paper, we develop the first deep learning‐based method for particle‐based rendering, and specifically focus on photon density estimation, the core of all particle‐based methods. We train a novel deep neural network to predict a kernel function to aggregate photon contributions at shading points. Our network encodes individual photons into per‐photon features, aggregates them in the neighborhood of a shading point to construct a photon local context vector, and infers a kernel function from the per‐photon and photon local context features. This network is easy to incorporate in many previous photon mapping methods (by simply swapping the kernel density estimator) and can produce high‐quality reconstructions of complex global illumination effects like caustics with an order of magnitude fewer photons compared to previous photon mapping methods. Our approach largely reduces the required number of photons, significantly advancing the computational efficiency in photon mapping.
An Adaptive BRDF Fitting Metric
Authors: Bieron J. , Peers P. 
Published: July 2020

AbstractWe propose a novel image‐driven fitting strategy for isotropic BRDFs. Whereas existing BRDF fitting methods minimize a cost function directly on the error between the fitted analytical BRDF and the measured isotropic BRDF samples, we also take into account the resulting material appearance in visualizations of the BRDF. This change of fitting paradigm improves the appearance reproduction fidelity, especially for analytical BRDF models that lack the expressiveness to reproduce the measured surface reflectance. We formulate BRDF fitting as a two‐stage process that first generates a series of candidate BRDF fits based only on the BRDF error with measured BRDF samples. Next, from these candidates, we select the BRDF fit that minimizes the visual error. We demonstrate qualitatively and quantitatively improved fits for the Cook‐Torrance and GGX microfacet BRDF models. Furthermore, we present an analysis of the BRDF fitting results, and show that the image‐driven isotropic BRDF fits generalize well to other light conditions, and that depending on the measured material, a different weighting of errors with respect to the measured BRDF is necessary.
Can't Invert the CDF? The Triangle‐Cut Parameterization of the Region under the Curve
Authors: Heitz E. 
Published: July 2020

AbstractWe present an exact, analytic and deterministic method for sampling densities whose Cumulative Distribution Functions (CDFs) cannot be inverted analytically. Indeed, the inverse‐CDF method is often considered the way to go for sampling non‐uniform densities. If the CDF is not analytically invertible, the typical fallback solutions are either approximate, numerical, or non‐deterministic such as acceptance‐rejection. To overcome this problem, we show how to compute an analytic area‐preserving parameterization of the region under the curve of the target density. We use it to generate random points uniformly distributed under the curve of the target density and their abscissae are thus distributed with the target density. Technically, our idea is to use an approximate analytic parameterization whose error can be represented geometrically as a triangle that is simple to cut out. This triangle‐cut parameterization yields exact and analytic solutions to sampling problems that were presumably not analytically resolvable.
Semi‐Procedural Textures Using Point Process Texture Basis Functions
Authors: Guehl P. , Allègre R. , Dischler J.‐M. , Benes B. , Galin E. 
Published: July 2020

AbstractWe introduce a novel semi‐procedural approach that avoids drawbacks of procedural textures and leverages advantages of data‐driven texture synthesis. We split synthesis in two parts: 1) structure synthesis, based on a procedural parametric model and 2) color details synthesis, being data‐driven. The procedural model consists of a generic Point Process Texture Basis Function (PPTBF), which extends sparse convolution noises by defining rich convolution kernels. They consist of a window function multiplied with a correlated statistical mixture of Gabor functions, both designed to encapsulate a large span of common spatial stochastic structures, including cells, cracks, grains, scratches, spots, stains, and waves. Parameters can be prescribed automatically by supplying binary structure exemplars. As for noise‐based Gaussian textures, the PPTBF is used as stand‐alone function, avoiding classification tasks that occur when handling multiple procedural assets. Because the PPTBF is based on a single set of parameters it allows for continuous transitions between different visual structures and an easy control over its visual characteristics. Color is consistently synthesized from the exemplar using a multiscale parallel texture synthesis by numbers, constrained by the PPTBF. The generated textures are parametric, infinite and avoid repetition. The data‐driven part is automatic and guarantees strong visual resemblance with inputs.
LncRNA GATA3‐AS1 facilitates tumour progression and immune escape in triple‐negative breast cancer through destabilization of GATA3 but stabilization of PD‐L1
Authors: Zhang Ming , Wang Ning , Song Peng , Fu Yingqiang , Ren Yanlv , Li Zhigao , Wang Jinsong 
Published: July 2020

AbstractObjectivesLong non‐coding RNAs (lncRNAs) have been demonstrated as crucial regulators in cancer, but whether they are involved in the immune response of cancer cells remains largely undiscovered. GATA3‐AS1 is a novel lncRNA that was upregulated in breast cancer (BC) according to online databases. However, its role in triple‐negative breast cancer (TNBC) was elusive.MethodsGATA3‐AS1 expression in BC tissues and adjacent normal tissues was obtained from online databases. Loss‐of‐function assays were designed and conducted to verify the functional role of GATA3‐AS1 in TNBC cells. Bioinformatic analysis and mechanism experiments were applied to explore the downstream molecular mechanism of GATA3‐AS1. Similarly, the upstream mechanism which led to the upregulation of GATA3‐AS1 in TNBC cells was also investigated.ResultsGATA3‐AS1 was markedly overexpressed in TNBC tissues and cells. Knockdown of GATA3‐AS1 suppressed TNBC cell growth and enhanced the resistance of TNBC cells to immune response. GATA3‐AS1 induced the deubiquitination of PD‐L1 through miR‐676‐3p/COPS5 axis. GATA3‐AS1 destabilized GATA3 protein by promoting GATA3 ubiquitination.ConclusionGATA3‐AS1 contributed to TNBC progression and immune evasion through stabilizing PD‐L1 protein and degrading GATA3 protein, offering a new target for the treatment of TNBC.
Phenotype of immunosuppression reduction after kidney transplantation
Authors: Posadas Salas Maria Aurora , Taber David , Soliman Karim , Nwadike Emmanuel , Srinivas Titte 
Published: July 2020

AbstractBackgroundImmunosuppressive regimens are delivered without direct measure of the net state of immunosuppression. Besides therapeutic drug monitoring, adjustments in immunosuppressive medications are largely event‐driven.MethodsWe studied the clinical phenotype of immunosuppression reduction (ISR) among kidney transplant recipients from 2005 to 2012. Patients were grouped into: no ISR, ISR for infection, or ISR for intolerance. Outcome measures were rejection, rejection‐free survival, and IFTA‐free survival.Results1114 adult kidney transplant recipients were included: 57% had no ISR, 16% had ISR for infection, and 27% had ISR for intolerance. ISR for infection was mainly on MMF, while ISR for intolerance was mainly on FK. ISR was associated with higher rates of acute rejection. The Kaplan‐Meier analysis showed increased prevalence of rejection among patients with ISR due to infection (P = .003) or intolerance (P = .05). The risk of interstitial fibrosis and tubular atrophy was increased in patients with ISR due to infection (P = .001) or intolerance (P = .018).ConclusionImmunosuppression reduction is associated with increased prevalence of rejection. The clinical phenotype of ISR is dominated by IFTA remote from the onset of ISR. Solely focusing on acute rejection may underestimate effects of ISR on long‐term graft function and survival.
The effects of prematurity and socioeconomic deprivation on early speech perception: A story of two different delays
Authors: Gonzalez‐Gomez Nayeli , O'Brien Frances , Harris Margaret 
Published: July 2020

AbstractThere is evidence showing that both maturational and environmental factors can impact on later language development. On the one hand, preterm birth has been found to increase the risk of deficits in the preschool and school years. Preterm children show poorer auditory discrimination, reading difficulties, poor vocabulary, less complex expressive language and lower receptive understanding than their matched controls. On the other hand, socioeconomic status (SES) indicators (i.e., income, education and occupation) have been found to be strongly related to linguistic abilities during the preschool and school years. However, there is very little information about how these factors result in lower linguistic abilities. The present study addresses this issue. To do so, we investigated early speech perception in full and preterm infants from families classed as high or low SES. Seventy‐six infants were followed longitudinally at 7.5, 9, 10.5 and 12 months of age. At each test point, three studies explored infants' phonetic, prosodic and phonotactic development respectively. Results showed no significant differences between the phonetic or the phonotactic development of the preterm and the full‐term infants. However, a time‐lag between preterm and full‐term developmental timing for prosody was found. Socioeconomic status did not have a significant effect on prosodic development. Nonetheless, phonetic and phonotactic development was affected by SES, infants from lower SES showed phonetic discrimination of non‐native contrast and a preference for high‐probability sequences later than their more advantaged peers. Overall these results suggest that different constraints apply to the acquisition of different phonological subcomponents.