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This perspective article acquaints readers with the creation of a professional community of practice around contemplative pedagogy (CP), a rationale for CP in libraries, and how CP and mindfulness ...

Purpose Cost-effectiveness evaluations of first-line genomic sequencing (GS) in the diagnosis of children with genetic conditions are limited by the lack of well-defined comparative cohorts. We sought to evaluate the cost-effectiveness of early GS in pediatric patients with complex monogenic conditions compared with a matched historical cohort. Methods Data, including investigation costs, were collected in a prospective cohort of 92 pediatric patients undergoing singleton GS over an 18-month period (2016-2017) with two of the following: a condition with high mortality, multisystem disease involving three or more organs, or severe limitation of daily function. Comparative data were collected in a matched historical cohort who underwent traditional investigations in the years 2012-2013. Results GS yielded a diagnosis in 42% while traditional investigations yielded a diagnosis in 23% (p = 0.003). A change in management was experienced by 74% of patients diagnosed following GS, compared with 32% diagnosed following traditional investigations. Singleton GS at a cost of AU$3100 resulted in a mean saving per person of AU$3602 (95% confidence interval [CI] AU$2520-4685). Cost savings occurred across all investigation subtypes and were only minimally offset by clinical management costs. Conclusion GS in complex pediatric patients saves significant costs and doubles the diagnostic yield of traditional approaches.

usc Refereed/Peer-reviewed Purpose: Genetic variants causing aberrant premessenger RNA splicing are increasingly being recognized as causal variants in genetic disorders. In this study, we devise standardized practices for polymerase chain reaction (PCR)-based RNA diagnostics using clinically accessible specimens (blood, fibroblasts, urothelia, biopsy). Methods: A total of 74 families with diverse monogenic conditions (31% prenatal-congenital onset, 47% early childhood, and 22% teenage-adult onset) were triaged into PCR-based RNA testing, with comparative RNA sequencing for 19 cases. Results: Informative RNA assay data were obtained for 96% of cases, enabling variant reclassification for 75% variants that can be used for genetic counseling (71%), to inform clinical care (32%) and prenatal counseling (41%). Variant-associated mis-splicing was highly reproducible for 28 cases with samples from ≥2 affected individuals or heterozygotes and 10 cases with ≥2 biospecimens. PCR amplicons encompassing another segregated heterozygous variant was vital for clinical interpretation of 22 of 79 variants to phase RNA splicing events and discern complete from partial mis-splicing. Conclusion: RNA diagnostics enabled provision of a genetic diagnosis for 64% of recruited cases. PCR-based RNA diagnostics has capacity to analyze 81.3% of clinically significant genes, with long amplicons providing an advantage over RNA sequencing to phase RNA splicing events. The Australasian Consortium for RNA Diagnostics (SpliceACORD) provide clinically-endorsed, standardized protocols and recommendations for interpreting RNA assay data.

The purpose of the study was to implement and prospectively evaluate the outcomes of a rapid genomic diagnosis program at two pediatric tertiary centers. Rapid singleton whole-exome sequencing (rWES) was performed in acutely unwell pediatric patients with suspected monogenic disorders. Laboratory and clinical barriers to implementation were addressed through continuous multidisciplinary review of process parameters. Diagnostic and clinical utility and cost-effectiveness of rWES were assessed. Of 40 enrolled patients, 21 (52.5%) received a diagnosis, with median time to report of 16 days (range 9–109 days). A result was provided during the first hospital admission in 28 of 36 inpatients (78%). Clinical management changed in 12 of the 21 diagnosed patients (57%), including the provision of lifesaving treatment, avoidance of invasive biopsies, and palliative care guidance. The cost per diagnosis was AU$13,388 (US$10,453). Additional cost savings from avoidance of planned tests and procedures and reduced length of stay are estimated to be around AU$543,178 (US$424,101). The clear relative advantage of rWES, joint clinical and laboratory leadership, and the creation of a multidisciplinary “rapid team” were key to successful implementation. Rapid genomic testing in acute pediatrics is not only feasible but also cost-effective, and has high diagnostic and clinical utility. It requires a whole-of-system approach for successful implementation.

Industrial scale injection of CO2 into the subsurface can result in significant fluid pressure increases, which can lead to potential environmental impacts such as caprock fracturing, fault activation and leakage into underground fresh water aquifers. Pressure management through brine extraction is an approach for managing formation pressure, effective stress, and plume movement in response to CO2 injection. However, the handling and management of the extracted brine has a cost that is added to carbon capture and sequestration (CCS) operations; therefore minimizing the extracted volume of brine can be of great importance. At the same time, economics of pressure management via brine extraction can be improved by treating the extracted high-salinity water and making it available for beneficial uses, for example as cooling water for power plants. In this paper, we introduce and demonstrate application of an adaptive reservoir management approach that optimizes extraction rates of reservoir brines for pressure control in an integrated optimization framework. Our approach will be tested during a brine extraction field experiment located in the southern United States, which is currently in the design and planning stages. The objective of the experiment is to evaluate the technical feasibility of managing subsurface pressures associated with large-scale CO2 injection volumes and to assess the cost and effectiveness of desalination technologies for saline waters containing high total dissolved solids (TDS). Our integrated adaptive management approach involves monitoring, model calibration, and optimization of brine extraction for pressure control. Based on measurements obtained during the injection phase and utilizing improved predictive models from repeated calibration, initial optimization calculations will be revised in regular intervals and the operating decisions for controlling and managing subsurface pressurization will be updated. In this paper, in preparation of the actual field demonstration, we investigate use of borehole measurements (i.e., pressure changes) and electromagnetic (EM) geophysical methods (i.e. salinity changes) in the adaptive management of the injection and brine extraction project. We also present a numerical exercise to investigate how the optimization performance is affected by the quality of initial site characterization data and by the frequency of dynamic model updates with newly acquired data during the injection. Our numerical study shows that more accurate initial reservoir characterization data reduce the risk of pressure buildup above a given maximum pressure because the optimization algorithm arrives at better estimates of initial extraction rates, which in turn results in better control of pressure during the overall injection times. Results also show that low frequencies of model calibration and optimization with the new data, especially at early injection periods, may lead to optimization problems, either because pressure buildup constraints are violated or excessively high extraction rates are proposed. These optimization problems can be eliminated if more frequent data collection and model calibration are conducted, especially at early injection times. Approaches such as adaptive pressure management may constitute an effective tool to manage pressure buildup under uncertain reservoir conditions by minimizing the brine extraction volumes while controlling pressure buildups. This will be demonstrated in the actual field study, with injection planned to start in early 2019.

This chapter addresses the creation of an online learning object built to engage and orient students to library resources, spaces, and support services. Developed in Articulate Storyline, the orientation follows two student characters as they navigate a virtual library environment. As students progress through three nonlinear modules, they are immersed in a variety of interactive learning activities where they must click, hover, drag, drop, and explore to proceed. They learn by listening, reading, and interacting with the content through scenario-based activities. Through collaboration with faculty and administration, and the employment of instructional design practices using the ADDIE (analysis, design, development, implementation, and evaluation) model, we ensured that the learning object was student-friendly and clearly aligned with course objectives. Now integrated as a mandatory component of our First-Year Experience seminar, assessment data demonstrates that students are truly engaged throughout the learning experience and have developed a more nuanced understanding of the role of libraries and librarians.

The current rate of cerebral palsy (CP) per live births in Australia is between 0.14% and 0.2%, worldwide the rate has been static for 60 years at 0.2%. Typically a CP diagnosis is delayed until around age 2 years; this delay decreases the likelihood of a long-term positive patient outcome. Current early detection is by visual examination of newborns 10 to 20 weeks post gestation. A screening program based on filming babies and processing the video via artificial intelligence (AI) will allow increased early detection and intervention. This paper outlines the practical development, and initial results from, a recurrent deep neural net solution for the classification of newborn videos, specifically targeting CP, using the largest fidgety movements dataset in Australia.

Summary There is a compelling case, based on research in statistics education, for first courses in statistical inference to be underpinned by a staged development path. Preferably over a number of years, students should begin working with precursor forms of statistical inference, much earlier than they now do. A side benefit is giving younger students more straightforward and more satisfying ways of answering interesting real world questions. We discuss the issues that are involved in formulating precursor versions of inference and then present some specific and highly visual proposals. These build on novel ways of experiencing sampling variation and have intuitive connections to the standard formal methods of making inferences in first university courses in statistics. Our proposal uses visual comparisons to enable the inferential step to be made without taking the eyes off relevant graphs of the data. This allows the time and conceptual distances between questions, data and conclusions to be minimized, so that the most critical linkages can be made. Our approach was devised for use in high schools but is also relevant to adult education and some introductory tertiary courses.

Nations, corporations and political organizations around the world today are forced to deal with an increasing number of security threats. As a result, various organizations must find ways to adequately equip and prepare themselves to handle numerous dangerous and life threatening circumstances. Virtual reality is an extremely important technology that can be used across a variety of different fields and for a number of diverse applications, ranging from simulation training to visualization tools, in order to prepare for and manage disaster situations. Head mounted display (HMD) virtual reality systems attempt visually to immerse the user in a virtual environment. However, it is well recognized that latency, the delay in responding to a user's head movement, is a major shortcoming that plagues immersive HMD virtual reality systems. Excessive latency destroys the illusion of reality that such systems attempt to present to the user. A hardware architecture known as the address recalculation pipeline (ARP) and a computer graphics rendering technique called priority rendering, were designed to reduce the end-to-end latency suffered by immersive HMD virtual reality systems. This paper discusses the benefits of using the ARP virtual reality system in addressing security threats and disaster situations.

Virtual Reality is an exciting new area of human-computer interaction. Its use depends critically on having extremely low response times of the virtual environment to user interaction. The problem of reducing the lag between the user's head position or orientation changing and the updating of the displayed view has been described as one of the grand challenges of computing. The techniques described here form the basis of a solution for this problem. A radical new approach to the problem is presented and the influence of human factors is also considerd.

Virtual reality systems are placing never before seen demands on computer graphics hardware, yet few graphics systems are designed specifically for virtural reality. An address recalculation pipeline is a graphics display controller specifically designed for use with head mounted virtual reality systems, it performs orientation viewport mapping after rendering which means the users head orientation does not need to be known accurately until less than a microsecond before the first pixel of an update frame is actually sent to the head mounted display device. As a result the user perceived latency to head rotations is minimal.Using such a controller with image composition it is possible to render different objects within the world at different rate, thus it is possible to concentrate the available rendering power on the sections of the scene that change the most. The concentration of rendering power is known as priority rendering. Reductions of one order of magnitude in the number of objects rendered for an entire scene have been observed when using priority rendering. When non interactive background scenes which are rendered with a high quality rendering algorithm such as ray tracing are added to the world, highly realistic virtual worlds are possible with little or no latency.

Language and the telling of data stories have fundamental roles in advancing the GAISE agenda of shifting the emphasis in statistics education from the operation of sets of procedures towards conceptual understanding and communication. In this paper we discuss some of the major issues surrounding story telling in statistics, challenge current practices, open debates about what constitutes good verbalization of structure in graphical and numerical summaries, and attempt to clarify what underlying concepts should be brought to students' attention, and how. Narrowing in on the particular problem of comparing groups, we propose that instead of simply reading and interpreting coded information from graphs, students should engage in understanding and verbalizing the rich conceptual repertoire underpinning comparisons using plots. These essential data-dialogues include paying attention to language, invoking descriptive and inferential thoughts, and determining informally whether claims can be made about the unde...

Computer simulations and animations for developing statistical concepts are often not understood by beginners. Hands-on physical simulations that morph into computer simulations are teaching approaches that can build students’ concepts. In this paper we review the literature on visual and verbal cognitive processing and on the efficacy of animations in promoting learning. We describe an instructional sequence, from hands-on to animations, developed for 14 year-old students. The instruction focused on developing students’ understanding of sampling variability and using samples to make inferences about populations. The learning trajectory from hands-on to animations is analyzed from the perspective of multimedia learning theories while the learning outcomes of about 100 students are explored, including images and reasoning processes used when comparing two box plots. The findings suggest that carefully designed learning trajectories can stimulate students to gain access to inferential concepts and reasoning processes. The role of verbal, visual, and sensory cues in developing students' reasoning is discussed and important questions for further research on these elements are identified.

Objective – Reflective assessment is an effective method of teacher evaluation, serving as an approach for assessing teaching practices, generating insights, and connecting with colleagues, ultimately supporting meaningful transformation of teaching practice. In this paper, three librarians model a reflective assessment approach in evaluating and improving their experiences implementing learner-driven teaching practices in credit-bearing courses in topics related to library and information studies. Methods – Following a model of reflective assessment, we asked ourselves how our practice can better support learner-driven teaching practices, thus assessing and improving our own teaching and improving students’ learning experiences. Our process involved five steps: cohere around shared viewpoints, identify teaching practices for reflection, conduct reflection, discuss and analyze reflections to produce insights, and apply insights to improve teaching. Results – We reflect on five different learner-driven teaching practices: co-creative syllabus design, learner-defined personal learning goals, soliciting and responding to learner feedback, interdisciplinary discussions and exercises, and self-evaluation. We discuss improvements and refinements that we implemented in response to our reflective assessment, including more frequent checking in with students; more clarity regarding self-evaluation and grading; one-on-one meetings with all students; allowing students to negotiate, discuss, and determine assignment deadlines and dates; more flexibility with students’ work products; and increased pedagogical transparency. As a further result, our reflective process models an approachable framework for engaging in reflective assessment. Conclusion – This paper presents a model for reflective assessment of teaching in an academic library. We present a discussion of learner-driven teaching practices, and we offer a practical pathway for other teachers and practitioners to assess their teaching. We find that reflective assessment is an effective and insightful approach for understanding and improving learner-driven teaching practices.