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A significant ongoing initiative is to identify the conditions under which financial education is most effective, as it has been shown to work much better in some circumstances than others. One factor to consider is mathematical capability, as it has been linked to improved financial knowledge and financial outcomes. In this paper, we investigated one aspect of math capability: math confidence (that is, self-reported math ability). We examined how this factor interacts with financial education (measured by the number of financial education courses taken) with data from the 2018 National Financial Capability Survey (NFCS). We found that both mathematical confidence and financial education were positively associated with financial behaviors and, moreover, that the effects were largely independent rather than acting as substitutes -- suggesting that future intervention work should consider both factors.

Multiple coronaviruses have emerged independently in the past 20 years that cause lethal human diseases. Although vaccine development targeting these viruses has been accelerated substantially, there remain patients requiring treatment who cannot be vaccinated or who experience breakthrough infections. Understanding the common host factors necessary for the life cycles of coronaviruses may reveal conserved therapeutic targets. Here, we used the known substrate specificities of mammalian protein kinases to deconvolute the sequence of phosphorylation events mediated by three host protein kinase families (SRPK, GSK-3, and CK1) that coordinately phosphorylate a cluster of serine and threonine residues in the viral N protein, which is required for viral replication. We also showed that loss or inhibition of SRPK1/2, which we propose initiates the N protein phosphorylation cascade, compromised the viral replication cycle. Because these phosphorylation sites are highly conserved across coronaviruses, inhibitors of these protein kinases not only may have therapeutic potential against COVID-19 but also may be broadly useful against coronavirus-mediated diseases.

Research on the role of the ballet pianist is limited. A gap in the literature concerns the ways in which dance instructors and accompanists 'make sense' of their collaboration. The working relationship between a dance teacher and a dance musician in a ballet class was investigated. The researcher, a ballet pianist, conducted a semi-structured, in-depth interview with a ballet-teacher colleague who is also a musician and composer. The data was analysed using Interpretative Phenomenological Analysis (IPA), a methodology which takes into account the interpretations of the participant (dance teacher) and the researcher (dance musician). This single case study presents three higher-order themes: 'the cycle of creativity' between the teacher, musician, and students; 'a tonic sense in the body' facilitated by the musician's playing; and 'the ideal situation' regarding the musician's sensory awareness during the class. It also reveals two subordinate themes that challenge effective relationships: the students' perceived response to percussion; and the teacher's use of recorded music. The results offer insight into specific perceptions and understandings that are transferable to dance teachers and dance musicians engaged in continuing professional development.

Recent research has shown that two forms of education intervention significantly improve financial outcomes: rigorous, in-depth personal finance courses and additional mathematics coursework. This suggests that a mathematics course that offered systematic, in-depth applications to personal finance could be particularly effective. In this article, we summarize the results from a pilot of such a course, and demonstrate how it is motivated by recent literature, despite being a type of course that has so far not been studied thoroughly. We then present the results of our preliminary impact assessment and show how financial knowledge and confidence improve significantly after taking the course. We discuss how this indicates that such an approach is a promising strategy for improving financial outcomes.

BackgroundPediatric anesthesiology has been greatly impacted by COVID-19 in the delivery of care to patients and to the individual providers. With this study, we sought to survey pediatric centers and highlight the variations in care related to perioperative medicine during the COVID-19 pandemic, including the availability of protective equipment, the practice of pediatric anesthesia, and economic impact.AimThe aim of the survey was to determine how COVID-19 directly impacted pediatric anesthesia practices during the study period.MethodsA survey concerning four major domains (testing, safety, clinical management/policy, economics) was developed. It was pilot tested for clarity and content by members of the Pediatric Anesthesia COVID-19 Collaborative. The survey was administered by email to all Pediatric Anesthesia COVID-19 Collaborative members on September 1, 2020. Respondents had six weeks to complete the survey and were instructed to answer the questions based on their institution's practice during September 1 - October 13, 2020.ResultsSixty-three institutions (100% response rate) participated in the COVID-19 Pediatric Anesthesia Survey. Forty-one hospitals (65%) were from the United States, and 35% included other countries. N95 masks were available to anesthesia teams at 91% of institutions (n = 57) (95% CI: 80%-96%). COVID-19 testing criteria of anesthesia staff and guidelines to return to work varied by institution. Structured simulation training aimed at improving COVID-19 safety and patient care occurred at 62% of institutions (n = 39). Pediatric anesthesiologists were economically affected by a reduction in their employer benefits and restriction of travel due to employer imposed quarantine regulations.ConclusionOur data indicate that the COVID-19 pandemic has impacted the testing, safety, clinical management, and economics of pediatric anesthesia practice. Further investigation into the long-term consequences for the specialty is indicated.

Canonical Wnt/β-catenin signaling is frequently dysregulated in myeloid leukemias and is implicated in leukemogenesis. Nuclear-localized β-catenin is indicative of active Wnt signaling and is frequently observed in acute myeloid leukemia (AML) patients; however, some patients exhibit little or no nuclear β-catenin even where cytosolic β-catenin is abundant. Control of the subcellular localization of β-catenin therefore represents an additional mechanism regulating Wnt signaling in hematopoietic cells. To investigate the factors mediating the nuclear-localization of β-catenin, we carried out the first nuclear/cytoplasmic proteomic analysis of the β-catenin interactome in myeloid leukemia cells and identified putative novel β-catenin interactors. Comparison of interacting factors between Wnt-responsive cells (high nuclear β-catenin) versus Wnt-unresponsive cells (low nuclear β-catenin) suggested the transcriptional partner, LEF-1, could direct the nuclear-localization of β-catenin. The relative levels of nuclear LEF-1 and β-catenin were tightly correlated in both cell lines and in primary AML blasts. Furthermore, LEF-1 knockdown perturbed β-catenin nuclear-localization and transcriptional activation in Wnt-responsive cells. Conversely, LEF-1 overexpression was able to promote both nuclear-localization and β-catenin-dependent transcriptional responses in previously Wnt-unresponsive cells. This is the first β-catenin interactome study in hematopoietic cells and reveals LEF-1 as a mediator of nuclear β- catenin level in human myeloid leukemia.

INTRODUCTION:Understanding the duration of pediatric general anesthesia exposure in contemporary practice is important for identifying groups at risk for long general anesthesia exposures and designing trials examining associations between general anesthesia exposure and neurodevelopmental outcomes. METHODS:We performed a retrospective cohort analysis to estimate pediatric general anesthesia exposure duration during 2010-2015 using the National Anesthesia Clinical Outcomes Registry. RESULTS:A total of 1 548 021 pediatric general anesthetics were included. Median general anesthesia duration was 57 minutes (IQR: 28-86) with 90th percentile 145 minutes. Children aged 3 hours. High ASA physical status and care at a university hospital were associated with longer exposure times. CONCLUSION:While the vast majority (94%) of children undergoing general anesthesia are exposed for

Instantaneous control over the orientation of anisotropically shaped plasmonic nanostructures allows for selective excitation of plasmon modes and enables dynamic tuning of the plasmonic properties. Herein we report the synthesis of rod-shaped magnetic/plasmonic core-shell nanocomposite particles and demonstrate the active tuning of their optical property by manipulating their orientation using an external magnetic field. We further design and construct an IR-photoelectric coupling system, which generates an output voltage depending on the extinction property of the measured nanocomposite sample. We employ the device to demonstrate that the nanocomposite particles can serve as units for information encryption when immobilized in a polymer film and additionally when dispersed in solution can be employed as a new type of magnetic-field-direction sensor.

Tubeless upper airway surgery in children is a complex procedure in which surgeons and anaesthetists share the same operating field. These procedures are often interrupted for rescue oxygen therapy. The efficacy of nasal high-flow oxygen to decrease the frequency of rescue interruptions in children undergoing upper airway surgery is unknown. In this multicentre randomised trial conducted in five tertiary hospitals in Australia, children aged 0–16 years who required tubeless upper airway surgery were randomised (1:1) by a web-based randomisation tool to either nasal high-flow oxygen delivery or standard oxygen therapy (oxygen flows of up to 6 L/min). Randomisation was stratified by site and age (<1 year, 1–4 years, and 5–16 years). Subsequent tubeless upper airway surgery procedures in the same child could be included if there were more than 2 weeks between the procedures, and repeat surgical procedures meeting this condition were considered to be independent events. The oxygen therapy could not be masked, but the investigators remained blinded until outcome data were locked. The primary outcome was successful anaesthesia without interruption of the surgical procedure for rescue oxygenation. A rescue oxygenation event was defined as an interruption of the surgical procedure to deliver positive pressure ventilation using either bag mask technique, insertion of an endotracheal tube, or laryngeal mask to improve oxygenation. There were ten secondary outcomes, including the proportion of procedures with a hypoxaemic event (SpO 2 <90%). Analyses were done on an intention-to-treat (ITT) basis. Safety was assessed in all enrolled participants. This trial is registered in the Australian New Zealand Clinical Trials Registry, ACTRN12618000949280, and is completed. From Sept 4, 2018, to April 12, 2021, 581 procedures in 487 children were randomly assigned to high-flow oxygen (297 procedures) or standard care (284 procedures); after exclusions, 528 procedures (267 assigned to high-flow oxygen and 261 assigned to standard care) in 483 children (293 male and 190 female) were included in the ITT analysis. The primary outcome of successful anaesthesia without interruption for tubeless airway surgery was achieved in 236 (88%) of 267 procedures on high-flow oxygen and in 229 (88%) of 261 procedures on standard care (adjusted risk ratio [RR] 1·02, 95% CI 0·96–1·08, p=0·82). There were 51 (19%) procedures with a hypoxaemic event in the high-flow oxygen group and 57 (22%) in the standard care group (RR 0·86, 95% CI 0·58–1·24). Of the other prespecified secondary outcomes, none showed a significant difference between groups. Adverse events of epistaxis, laryngospasm, bronchospasm, hypoxaemia, bradycardia, cardiac arrest, hypotension, or death were similar in both study groups. Nasal high-flow oxygen during tubeless upper airway surgery did not reduce the proportion of interruptions of the procedures for rescue oxygenation compared with standard care. There were no differences in adverse events between the intervention groups. These results suggest that both approaches, nasal high-flow or standard oxygen, are suitable alternatives to maintain oxygenation in children undergoing upper airway surgery. Thrasher Research Fund, the Australian and New Zealand College of Anaesthetists, the Society for Paediatric Anaesthesia in New Zealand and Australia. [ABSTRACT FROM AUTHOR]

Multisplit is a broadly useful parallel primitive that permutes its input data into contiguous buckets or bins, where the function that categorizes an element into a bucket is provided by the programmer.Due to the lack of an efficient multisplit on GPUs, programmers often choose to implement multisplit with a sort. However, sort does more work than necessary to implement multisplit, and is thus inefficient.In this work, we provide a parallel model and multiple implementations for the multisplit problem. Our principal focus is multisplit for a small number of buckets.In our implementations, we exploit the computational hierarchy of the GPU to perform most of the work locally, with minimal usage of global operations.We also use warp-synchronous programming models to avoid branch divergence and reduce memory usage, as well as hierarchical reordering of input elements to achieve better coalescing of global memory accesses.On an NVIDIA K40c GPU, for key-only (key-value) multisplit, we demonstrate a 3.0--6.7x (4.4--8.0x) speedup over radix sort, and achieve a peak throughput of 10.0 G keys/s.

For large-scale graph analytics on the GPU, the irregularity of dataaccess/control flow and the complexity of programming GPUs have been twosignificant challenges for developing a programmable high-performance graphlibrary. "Gunrock," our high-level bulk-synchronous graph-processing systemtargeting the GPU, takes a new approach to abstracting GPU graph analytics:rather than designing an abstraction around computation, Gunrock insteadimplements a novel data-centric abstraction centered on operations ona vertex or edge frontier. Gunrock achieves a balance between performance andexpressiveness by coupling high-performance GPU computing primitives andoptimization strategies with a high-level programming model that allowsprogrammers to quickly develop new graph primitives with small code size andminimal GPU programming knowledge. We evaluate Gunrock on five graphprimitives (BFS, BC, SSSP, CC, and PageRank) and show that Gunrock has onaverage at least an order of magnitude speedup over Boost and PowerGraph,comparable performance to the fastest GPU hardwired primitives, and betterperformance than any other GPU high-level graph library.

Finding the shortest paths from a single source to all other vertices is a fundamental method used in a variety of higher-level graph algorithms. We present three parallel friendly and work-efficient methods to solve this Single-Source Shortest Paths (SSSP) problem: Workfront Sweep, Near-Far and Bucketing. These methods choose different approaches to balance the tradeoff between saving work and organizational overhead. In practice, all of these methods do much less work than traditional Bellman-Ford methods, while adding only a modest amount of extra work over serial methods. These methods are designed to have a sufficient parallel workload to fill modern massively-parallel machines, and select reorganizational schemes that map well to these architectures. We show that in general our Near-Far method has the highest performance on modern GPUs, outperforming other parallel methods.We also explore a variety of parallel load-balanced graph traversal strategies and apply them towards our SSSP solver. Our work-saving methods always outperform a traditional GPU Bellman-Ford implementation, achieving rates up to 14x higher on low-degree graphs and 340x higher on scalefree graphs. We also see significant speedups (20–60x) when compared against a serial implementation on graphs with adequately high degree.

In this work, we introduced k-d darts as a particular type of higherdimensional sampling. We described a k-d dart framework for hyperplanes of general dimension k, and then demonstrated efficiency and accuracy over three applications using k = 1, and accuracy for one application using k = 1. In particular, darts produce accurate estimates of the volume of an object regardless of the dimension, orientation, and aspect ratio of the object. Axis-aligned darts are universally preferable to unaligned ones for sampling square domains, and we expect this to extend to hyperrectangles, such as bounding boxes. Darts also produce accurate mean estimates for function integration. © 2014 ACM 0730-0301/2014/01-ART3 15.00.

• Patients with aneurysmal subarachnoid haemorrhage (aSAH) who undergo decompressive craniectomy (DC) are at greater risk of unfavourable outcome compared with those don't. • Associated intracerebral haemorrhage and increased mid-line shift are predictive of undergoing a DC in patients with aSAH. • Higher WFNS grade and the presence of a delayed ischaemic neurological deficit requiring endovascular angioplasty are associated with unfavourable outcome among aSAH patients undergoing decompressive surgery. Decompressive craniectomy (DC) remains a controversial intervention for intracranial hypertension among patients with aneurysmal subarachnoid haemorrhage (aSAH). We identified aSAH patients who underwent DC following microsurgical aneurysm repair from a prospectively maintained registry and compared their outcomes with a propensity-matched cohort who did not. Logistic regression was used to identify predictors of undergoing decompressive surgery and post-operative outcome. Outcomes of interest were inpatient mortality, unfavourable outcome, NIS-Subarachnoid Hemorrhage Outcome Measure and modified Rankin Score (mRS). A total of 246 patients with aSAH underwent clipping of the culprit aneurysm between 01/09/2011 and 20/07/2020. Of these, 46 underwent DC and were included in the final analysis. Unsurprisingly, DC patients had a greater chance of unfavourable outcome (p < 0.001) and higher median mRS (p < 0.001) at final follow-up. Despite this, almost two-thirds (64.1 %) of DC patients had a favourable outcome at this time-point. When compared with a propensity-matched cohort who did not, patients treated with DC fared worse at all endpoints. Multivariable logistic regression revealed that the presence of intracerebral haemorrhage and increased pre-operative mid-line shift were predictive of undergoing DC, and WFNS grade ≥ 4 and a delayed ischaemic neurological deficit requiring endovascular angioplasty were associated with an unfavourable outcome. Our data suggest that DC can be performed with acceptable rates of morbidity and mortality. Further research is required to determine the superiority, or otherwise, of DC compared with structured medical management of intracranial hypertension in this context, and to identify predictors of requiring decompressive surgery and patient outcome. [ABSTRACT FROM AUTHOR]

We present parallel algorithms and implementations of a bzip2-like lossless data compression scheme for GPU architectures. Our approach parallelizes three main stages in the bzip2 compression pipeline: Burrows-Wheeler transform (BWT), move-to-front transform (MTF), and Huffman coding. In particular, we utilize a two-level hierarchical sort for BWT, design a novel scan-based parallel MTF algorithm, and implement a parallel reduction scheme to build the Huffman tree. For each algorithm, we perform detailed performance analysis, discuss its strengths and weaknesses, and suggest future directions for improvements. Overall, our GPU implementation is dominated by BWT performance and is 2.78x slower than bzip2, with BWT and MTF-Huffman respectively 2.89x and 1.34x slower on average. © 2012 IEEE.

We provide a simple algorithm and data structures for d-dimensional unbiased maximal Poisson-disk sampling. We use an order of magnitude less memory and time than the alternatives. Our results become more favorable as the dimension increases. This allows us to produce bigger samplings. Domains may be non-convex with holes. The generated point cloud is maximal up to round-off error. The serial algorithm is provably bias-free. For an output sampling of size n in fixed dimension d, we use a linear memory budget and empirical Θ(n) runtime. No known methods scale well with dimension, due to the "curse of dimensionality." The serial algorithm is practical in dimensions up to 5, and has been demonstrated in 6d. We have efficient GPU implementations in 2d and 3d. The algorithm proceeds through a finite sequence of uniform grids. The grids guide the dart throwing and track the remaining disk-free area. The top-level grid provides an efficient way to test if a candidate dart is disk-free. Our uniform grids are like quadtrees, except we delay splits and refine all leaves at once. Since the quadtree is flat it can be represented using very little memory: we just need the indices of the active leaves and a global level. Also it is very simple to sample from leaves with uniform probability. © 2012 The Author(s).

We design a high-performance parallel merge sort for highly parallel systems. Our merge sort is designed to use more register communication (not shared memory), and does not suffer from over-segmentation as opposed to previous comparison based sorts. Using these techniques we are able to achieve a sorting rate of 250 MKeys/sec, which is about 2.5 times faster than Thrust merge sort performance, and 70% faster than non-stable state-of-the-art GPU merge sorts. Building on this sorting algorithm, we develop a scheme for sorting variable-length key/value pairs, with a special emphasis on string keys. Sorting non-uniform, unaligned data such as strings is a fundamental step in a variety of algorithms, yet it has received comparatively little attention. To our knowledge, our system is the first published description of an efficient string sort for GPUs. We are able to sort strings at a rate of 70 MStrings/s on one dataset and up to 1.25 GB/s on another dataset using a GTX 580.

We present a multi-stage method for solving large tridiagonal systems on the GPU. Previously large tridiagonal systems cannot be efficiently solved due to the limitation of onchip shared memory size. We tackle this problem by splitting the systems to smaller ones and then solving them on-chip. The multi-stage characteristic of our method, together with various workloads and GPUs of different capabilities, obligates an auto-tuning strategy to carefully select the switch points between computation stages. In particular, we show two ways to effectively prune the tuning space and thus avoid an impractical exhaustive search: (1) apply algorithmic knowledge to decouple tuning parameters, and (2) estimate search starting points based on GPU architecture parameters. We demonstrate autotuning is a powerful tool that improves the performance by up to 5x, saves 17% and 32% of execution time on average respectively for static and dynamic tuning, and enables our multi-stage solver to outperform the Intel MKL tridiagonal solver on many parallel tridiagonal systems by 5-11x.

We generalize a method for avoiding GPU shared communication when dealing with a downsweep pattern. We apply this generalization to Cyclic Reduction, a tridiagonal solver with this pattern. Previously, Cyclic Reduction suffered poor performance when compared to other tridiagonal solvers on the GPU due to performance issues stemming from shared memory bandwidth bottlenecks and step-efficiency. We address this problem by applying our downsweep shared-memory communication reducing methodology. Our re-mapping also allows Cyclic Reduction to solve larger systems directly in a virtual block. By using our generalized mapping, we improve Cyclic Reduction's performance on a GPU by a factor of 3--4.5x over the original CR implementation, making it 1.5--3x faster than other GPU tridiagonal solvers.

We solve the problem of generating a uniform Poisson-disk sampling that is both maximal and unbiased over bounded non-convex domains. To our knowledge this is the first provably correct algorithm with time and space dependent only on the number of points produced. Our method has two phases, both based on classical dart-throwing. The first phase uses a background grid of square cells to rapidly create an unbiased, near-maximal covering of the domain. The second phase completes the maximal covering by calculating the connected components of the remaining uncovered voids, and by using their geometry to efficiently place unbiased samples that cover them. The second phase converges quickly, overcoming a common difficulty in dart-throwing methods. The deterministic memory is O(n) and the expected running time is O(n log n), where n is the output size, the number of points in the final sample. Our serial implementation verifies that the log n dependence is minor, and nearly O(n) performance for both time and memory is achieved in practice. We also present a parallel implementation on GPUs to demonstrate the parallel-friendly nature of our method, which achieves 2.4x the performance of our serial version.

This article discusses the importance of increasing access to new therapies for Australian children and adolescents through clinical trials. It emphasizes the need for investment and a coordinated national approach to ensure that Australian children do not fall behind their international peers. The article highlights the benefits of collaborative approaches and strategic investment in pediatric clinical trials, as well as the challenges in delivering high-quality trials in this population. It acknowledges the additional challenges faced in Australia due to distance and regulatory factors, and calls for equitable access to emerging treatments for all Australian children, regardless of their circumstances. The article concludes by emphasizing the need for national investment in pediatric clinical trial delivery in Australia. [Extracted from the article]