ANU Research Publications
Permanent URI for this collectionhttps://hdl.handle.net/1885/26
The Australian National University's Research Publications collection is an online location for collecting, preserving and disseminating the scholarly output of the University. This service allows members of the University to share their research with the wider community. ANU Open Research accepts journal articles, conference papers, book chapters, working or technical papers and other forms of scholarly communication.
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Item type: Publication , Access status: Metadata only , Short-term outcomes of infants of substance-using mothers admitted to neonatal intensive care units in New South Wales and the Australian Capital Territory(2007) Abdel-Latif, Mohamed E.; Bajuk, Barbara; Lui, Kei; Oei, JuleeAim: Illicit substance use during pregnancy is associated with an increased rate of perinatal complications. Our study examines if outcome of infants of substance-using mothers (ISMs) in the neonatal intensive care unit (NICU) setting is similar to unexposed infants (controls).Methods: A prospective state-wide NICU study comparing ISMs to control infants admitted to 10 NICUs during a 3-years period (2001-2003). An ISM was defined as an infant whose mother admitted to or was documented to have used substances of dependency (illicit or otherwise) during this pregnancy.Results: There was a preponderance towards prematurity with ISMs comprising 5.1% (n = 310) of 6120 high risk infants (6.2% (n = 165) < 32 weeks gestation and 6.8% (n = 39) of 22-26 weeks gestation). More ISMs were outborn and had significantly lower mortality rate, particularly in the < 32 week gestation subgroup (adjusted OR 0.517 95% CI 0.277-0.962, P < 0.037). ISMs also demonstrated a non-significant trend towards an increased risk of neonatal morbidities. The pattern of rural and urban substance use was different, with a higher incidence of opiate use (49.3% vs. 26.9%, P < 0.001) in urban areas. Most opiate using mothers (85.6%), irrespective of rural or urban residence, were enrolled in methadone programmes. ISMs had a higher incidence of antepartum haemorrhage and chorioamnionitis and fewer were given antenatal steroids.Conclusion: ISMs are common in the high-risk NICU population. Further studies are needed to confirm the lower mortality rate and long-term outcomes in these infants.Item type: Publication , Access status: Metadata only , Underlying beliefs linked to public opinion about gene drive and pest-specific toxin for pest control(2020) MacDonald, Edith A; Edwards, Eric; Balanovic, Jovana; Medvecky, FabienItem type: Publication , Access status: Metadata only , What Does It Take to Train and Support Facilitators to Deliver Cse Effectively in Out-of-school Settings for Young People with Particular Needs and Circumstances?: Lessons Learned From a Multi-country Implementation Research Study(2024) Plesons, Marina; De Meyer, Sara; Chandra-Mouli, Venkatraman; Vega Casanova, Jair; Adrians Pacheco, Karen; Perez Quintero, Camilo; Buitrago Rovira, Natalia; Pincock, Kate; Yadete, Workneh; Jones, Nicola; Amo-Adjei, Joshua; Agbemavi, Wonder; Mhango, Patani; Chipeta, Effie; Mtende, Medrina; Malata, Monica; Bjartnes, Kristine; Mladenov, Petar; Zhukov, IlyaItem type: Publication , Access status: Metadata only , Culturing life: how cells became technology by Hannah Landecker(2010) Parry, BronwynItem type: Publication , Access status: Metadata only , Comprehensive portrait of canonical and non-canonical splicing in cancer(2018) Jayasinghe, Reyka G.; Cao, Song; Gao, Qingsong; Wyczalkowski, Matthew A.; Sengupta, Sohini; Walter, Matthew J.; Maher, Christopher; Wendl, Michael C.; Chen, Feng; Eyras, Eduardo; Lazar, Alexander J.; Chen, Ken; Shmulevich, Ilya; Ding, LiItem type: Publication , Access status: Metadata only , Integrated deep learning model for predicting DNA methylation and tumor types from histopathology in central nervous system tumors(2024-03-15) Shulman, Eldad David; Hoang, Danh-Tai; Turakulov, Rust; Abdullaev, Zied; Singh, Omkar; Campagnolo, Emma M.; Stone, Eric A.; Nasrallah, MacLean P.; Ruppin, Eytan; Aldape, KennethPrecision in diagnosis of diverse central nervous system (CNS) tumor types is crucial for optimal patient treatment. DNA methylation profiles, which capture the methylation status of thousands of individual CpG sites, are data-driven means to enhance diagnostic accuracy, but this technique is expensive, time-consuming, and not yet routinely available. To address this, we developed DEPLOY, a deep-learning model that predicts 10 major categories of CNS tumors from histopathology. DEPLOY integrates three distinct components: the first classifies CNS tumors directly from histopathology slide images (‘direct model’); the second initially generates predictions for DNA methylation beta values, which are subsequently used for tumor classification (‘indirect model’); and the third classifies tumor types directly from routinely available patient demographics. First, we find that DEPLOY accurately predicted beta values from histopathology images, suggesting that application of inferred methylation data is a promising approach for deep learning histopathology-based classifiers. Using a 10-class model trained on an internal dataset, we apply this model on two independent external test datasets of 1,522 and 348 cases, achieving top-1 accuracies of 96% and 94%, respectively on samples which are predicted with high confidence. Taken together, DEPLOY could assist pathologists in diagnosing CNS tumors, in an equitable very low-cost manner, within a clinically relevant short time frame.Item type: Publication , Access status: Metadata only , Intra-household Differences in Education and Home Leaving in Indonesia(2006) Witoelar, FirmanThis paper investigates some of the underlying factors determining the probability of household division, defined here as the event when an adult leaves his or her original household, utilizing data from two waves of the IFLS (IFLS1-1993 and IFLS3-2000). Borrowing the empirical framework suggested by Foster and Rosenzweig (2002), I estimate the probability of household division by the subsequent waves of the survey, using household variables from an earlier wave as the explanatory variables. The findings suggest that education variables play an important albeit limited role in determining household division. There is evidence that higher education of the household head is associated with lower propensity of an adult household member to leave. On the other hand, higher maximum years of schooling of other members in the household are associated with higher probability of household division. These results, along with the finding showing that rural households are more likely to divide, indicate that household division in Indonesia may largely be associated with the mobility of young, more educated members from rural areas. While the empirical framework is based on a collective household model, the results can also be explained within the context of unitary household model.Item type: Publication , Access status: Metadata only , Book review: Commodities and Colonialism: The Story of Big Sugar in Indonesia, 1880–1942, by G.R. Knight(2014) van der Eng, PierreItem type: Publication , Access status: Metadata only , Witch-hunt and conspiracy: the “ninja case” in East Java(2016-11-03) Sastrawan, Wayan JarrahItem type: Publication , Access status: Metadata only , Book review: Bibliography of Soil Science in Indonesia 1890-1963, by S.M. Chin A Tam(1994) van der Eng, PierreItem type: Publication , Access status: Metadata only , Cornerstone of the nation: the defense industry and the building of modern Korea under Park Chung Hee(2024-12-12) Lee, DongkeunItem type: Publication , Access status: Metadata only , Item type: Publication , Access status: Metadata only , Spectral factorization of time-varying covariance functions(1969) Anderson, Brian; Moore, Jofin B.; Loo, Sonny G.The determination of the state-space equations of a time-varying finite-dimensional linear system with a prescribed output covariance matrix is considered when the system is excited by Gaussian white-noise inputs. It is shown that a symmetric state covariance matrix provides the key link between the state-space equations of a system and the system output covariance matrix. Furthermore, such a matrix satisfies a linear matrix differential equation if the state-space equations of the system are known, and a matrix Riccati equation if the output covariance matrix of the system is given. Existence results are given for the Riccati equation solution, and discussion of asymptotic solutions of the differential equations is also included.Item type: Publication , Access status: Metadata only , Assessing the Use of Virtual Reality as a Tool for Teaching Body Responses to Hypoxia in Pre-clinical Medical Education: A Mixed-Methods Study Focusing on Student Experience and Learning(2024-05-21) Estaphan, Suzanne; Lim, Jiahui JuliaVirtual reality (VR) has revolutionized medical education, yet its specific effcacy in teaching medical physiology remains underexplored. Conveying the complexities of physiological responses to hypoxia through traditional teaching methods poses logistical challenges, potentially hindering students’ deep understanding. This study investigates the impact of incorporating VR into pre-clinical medical physiology teaching, focusing on students’ self-reported 1) knowledge acquisition and understanding of body responses to hypoxia, 2) VR technology acceptance and satisfaction, and 3) overall learning experience. Methods: In 2022, an ANU Medical School teaching enhancement grant funded data collection to develop a comprehensive storyboard for a VR hypoxia simulation program. With support from the school’s Technology-enhanced Learning and Teaching team and the university’s Centre for Learning and Teaching, we created an in-house limited prototype focusing on key aspects of the scripted VR simulation program to test its feasibility and perceived usefulness within our MCHD program. The tool was integrated into a year 1 practical session, followed by a two-part series of data collection, comprising a questionnaire and video interviews. The questionnaire used a mixed-methods approach, including 5-point Likert scale closed-ended questions rating VR perceived usefulness and ease of use, and open-ended questions allowing participants to provide qualitative responses. Interviews delved deeper into users’ experience, interactivity, collaboration, realism, practicality, knowledge acquisition, improvement suggestions, and overall technology and learning satisfaction. Results: Although the implemented intervention did not represent the full range of features envisioned for the final program, preliminary findings from the first round of data collection via questionnaires (n=45/96) reported positive user experiences. Sixty percent of responses showed agreement (agree (n=22) and strongly agree (n=5)) that learning outcomes were clear and aided by VR. Qualitative findings revealed higher motivation to use VR for learning and an intuitive interface. Thematic analysis identified improvement opportunities, including enhancing hypoxia symptom discernibility and refining visual resolution. These insights will inform the next study phase, refining features to improve the overall learning experience and address technical challenges. Conclusion: Grounded in constructivist learning theory and technology acceptance frameworks, our findings leverage realistic VR simulations to enhance knowledge acquisition and understanding of complex physiological responses.Item type: Publication , Access status: Metadata only , Prehistoric Contacts in the Cook Islands(1974) Bellwood, PeterItem type: Publication , Access status: Metadata only , Managing patients with cutaneous squamous cell carcinoma metastatic to the axilla or groin lymph nodes(2010) Goh, Amy; Howle, Julie; Hughes, Michael; Veness, Michael J.Cutaneous squamous cell carcinoma accounts for 20% of all non-melanoma skin cancer with a minority arising on the trunk and extremities. A small proportion will develop metastases to regional nodes of the axilla or groin. We performed a retrospective review of patients with metastatic cutaneous squamous cell carcinoma to the axilla and groin treated at Westmead Hospital, Sydney. The purpose of this study was to document the treatment and outcome of these patients. We identified 18 men and 8 women with a median age of 73 years. Median follow-up was 18.5 months. Median lesion size was 27 mm (range 3-130 mm) and median thickness was 7 mm (range 3-32 mm). Nine patients developed metastases to the groin, 14 to the axilla, 1 in the epitrochlear, and 2 to both the epitrochlear and axillary lymph nodes. All patients were treated with surgery +/- radiotherapy. Recurrence developed in seven patients (27%) with most developing distant metastases. Most (6/7) patients with recurrence died. Predicting patients that may develop nodal metastatic non-head and neck cutaneous squamous cell carcinoma is difficult. Following diagnosis, surgery remains the primary treatment and select patients with unfavourable features, such as extranodal spread, may benefit from the addition of adjuvant radiotherapy.Item type: Publication , Access status: Metadata only , Modeling and Learning on High-Dimensional Matrix-Variate Sequences(2024) Zhang, Xu; Liu, Catherine C.; Guo, Jianhua; Yuen, K. C.; Welsh, A. H.We propose a new matrix factor model, named RaDFaM, which is strictly derived from the general rank decomposition and assumes a high-dimensional vector factor model structure for each basis vector. RaDFaM contributes a novel class of low-rank latent structures that trade off between signal intensity and dimension reduction from a tensor subspace perspective. Based on the intrinsic separable covariance structure of RaDFaM, for a collection of matrix-valued observations, we derive a new class of PCA variants for estimating loading matrices, and sequentially the latent factor matrices. The peak signal-to-noise ratio of RaDFaM is proved to be superior in the category of PCA-type estimators. We also establish an asymptotic theory including the consistency, convergence rates, and asymptotic distributions for components in the signal part. Numerically, we demonstrate the performance of RaDFaM in applications such as matrix reconstruction, supervised learning, and clustering, on uncorrelated and correlated data, respectively. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.Item type: Publication , Access status: Metadata only , Large-scale analysis of genome and transcriptome alterations in multiple tumors unveils novel cancer-relevant splicing networks (vol 26, pg 732, 2016)(2018) Sebestyen, Endre; Singh, Babita; Minana, Belen; Pages, Amadis; Mateo, Francesca; Pujana, Miguel Angel; Valcarcel, Juan; Eyras, EduardoItem type: Publication , Access status: Metadata only , Item type: Publication , Access status: Metadata only , Hate working weekends? Try a time tracker(2023-03-23) Mewburn, Inger