cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Additional file 12 of Comprehensive genomic characterization of NAC transcription factor family and their response to salt and drought stress in peanut
Creators: name: Yuan, Cuiling
name: Li, Chunjuan
name: Lu, Xiaodong
name: Zhao, Xiaobo
name: Yan, Caixia
name: Wang, Juan
name: Sun, Quanxi
name: Shan, Shihua
Publisher: name: figshare
Year: 2020
Subjects: subject: Genetics
subject: FOS: Biological sciences

description: Additional file 12. Number of different cis-acting elements present within the promoter of NAC genes.
Longitudinally Guided Super-Resolution of Neonatal Brain Magnetic Resonance Images
Creators: name: Cheng, Jian
name: Shen, Dinggang
name: Wang, Li
name: Zhang, Yongqin
name: Yap, Pew-Thian
name: Shi, Feng
Publisher: name: Institute of Electrical and Electronics Engineers (IEEE)
Year: 2018

description: Neonatal magnetic resonance (MR) images typically have low spatial resolution and insufficient tissue contrast. Interpolation methods are commonly used to upsample the images for the subsequent analysis. However, the resulting images are often blurry and susceptible to partial volume effects. In this paper, we propose a novel longitudinally guided super-resolution (SR) algorithm for neonatal images. This is motivated by the fact that anatomical structures evolve slowly and smoothly as the brain develops after birth. We propose a strategy involving longitudinal regularization, similar to bilateral filtering, in combination with low-rank and total variation constraints to solve the ill-posed inverse problem associated with image SR. Experimental results on neonatal MR images demonstrate that the proposed algorithm recovers clear structural details and outperforms state-of-the-art methods both qualitatively and quantitatively.
Ecological preferences of Hyla molleri in the colonisation of arboreal refuges in a human-shaped wetland. Supplementary Material
Creators: name: Vale, Rita L
name: Torres, Inês
name: Gomes, Sara
name: Fonseca, Carlos
name: Ferreira, Eduardo
Publisher: name: Brill Online
Year: 2018
Subjects: subject: 60201 Behavioural Ecology
subject: FOS: Biological sciences
subject: 60204 Freshwater Ecology
subject: 60208 Terrestrial Ecology
subject: Zoology

description: Hyla molleri is well adapted to arboreal microhabitats, which are used among breeding seasons. This species is common in wetlands across the Iberian Peninsula and is therefore vulnerable to the loss and degradation of these ecosystems. Due to its secretive habits, the knowledge about the ecology of H. molleri, outside the breeding season, is still scarce. Using artificial refuges as a proxy to natural refuges, we studied how H. molleri uses arboreal microhabitats near reproductive areas and which environmental drivers influence refuge colonisation. We installed 70 PVC pipe refuges in isolated trees and tree patches. Pairs of pipes were installed at two different heights and monitored fortnightly, for four consecutive days, for one year. Each sampling day, we registered the values of variables related with seasonality, microhabitat, dominant plant species, weather and site fidelity. We recorded 2234 individual colonization events by H. molleri, including 516 multiple colonization events, with a maximum of nine individuals in a single refuge. Refuges that were colonized before were more likely to be colonized again. Additionally, colonization was lower in spring and summer and higher in tree clusters than in isolated trees. We found no significant differences on the height or temperature of colonized versus non-colonized refuges. Our results highlight the importance of adequate arboreal microhabitats and the need for the conservation of terrestrial habitats around breeding areas. We also show that artificial refuges can be useful for H. molleri and similar species, namely for habitat improvement or the implementation of citizen-science and monitoring programs.
The Muirhead-Rado inequality, 1 Vector majorization and the permutohedron
Creators: name: Nathanson, Melvyn B.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Combinatorics (math.CO)
subject: FOS: Mathematics
subject: 05E05, 11B83, 15B51, 26D05, 26D15, 52A20, 52A30, 52A40

description: Let $\mathbf{a}$ and $\mathbf{b}$ be vectors in $\mathbf{R}^n$ with nonnegative coordinates. Permuting the coordinates, we can assume that $a_1 \geq \cdots \geq a_n$ and $b_1 \geq \cdots \geq b_n$. The vector $\mathbf{a}$ majorizes the vector $\mathbf{b}$, denoted $\mathbf{b} \preceq \mathbf{a}$, if $\sum_{i=1}^n b_i = \sum_{i=1}^n a_i$ and $\sum_{i=1}^k b_i \leq \sum_{i=1}^k a_i$ for all $k \in \{1,\ldots,n-1\}$. This paper proves theorems of Hardy-Littlewood-Pólya and Rado that $\mathbf{b} \preceq \mathbf{a}$ if and only if $P\mathbf{a} = \mathbf{b}$ for some doubly stochastic matrix $P$ if and only if $\mathbf{b}$ is in the $S_n$-permutohedron generated by $\mathbf{a}$.
description: 22 pages
Looking beyond facilities to eliminate vertical transmission
Creators: name: Rosenberg, Nora E
name: Chi, Benjamin H
Publisher: name: Elsevier
Year: 2022

description: In The Lancet HIV , Goodluck Willey Lyatuu and colleagues present large-scale estimates of vertical HIV transmission in Dar es Salaam, Tanzania. The authors prospectively follow a cohort of women who presented for antenatal care from 2015 to 2017 and estimate vertical transmission rates in their infants up to 18-months post-partum. Of 13,251 women followed over this period, 159 infants were diagnosed with HIV, representing an impressively low vertical transmission rate of 1·4%. Factors related to poor care-seeking and adherence behaviours were most strongly associated with vertical transmission: late presentation to antenatal care, lack of previous ART use, advanced HIV disease, and use of second-line ART regimens.
Low-frequency direct cortical stimulation of left superior frontal gyrus enhances working memory performance
Creators: name: Lustenberger, Caroline
name: Alagapan, Sankaraleengam
name: Froehlich, Flavio
name: Hadar, Eldad
name: Shin, Hae Won
Publisher: name: Elsevier
Year: 2018

description: The neural substrates of working memory are spread across prefrontal, parietal and cingulate cortices and are thought to be coordinated through low frequency cortical oscillations in the theta (3–8 Hz) and alpha (8–12 Hz) frequency bands. While the functional role of many subregions have been elucidated using neuroimaging studies, the role of superior frontal gyrus (SFG) is not yet clear. Here, we combined electrocorticography and direct cortical stimulation in three patients implanted with subdural electrodes to assess if superior frontal gyrus is indeed involved in working memory. We found left SFG exhibited task-related modulation of oscillations in the theta and alpha frequency bands specifically during the encoding epoch. Stimulation at the frequency matched to the endogenous oscillations resulted in reduced reaction times in all three participants. Our results provide evidence for SFG playing a functional role in working memory and suggest that SFG may coordinate working memory through low-frequency oscillations thus bolstering the feasibility of using intracranial electric stimulation for restoring cognitive function.
Low-rank dimensionality reduction for multi-modality neurodegenerative disease identification
Creators: name: Shen, Dinggang
name: Suk, Heung-Il
name: Zhu, Xiaofeng
Publisher: name: Springer Nature
Year: 2018

description: In this paper, we propose a novel dimensionality reduction method of taking the advantages of the variability, sparsity, and low-rankness of neuroimaging data for Alzheimer's Disease (AD) classification. We first take the variability of neuroimaging data into account by partitioning them into sub-classes by means of clustering, which thus captures the underlying multi-peak distributional characteristics in neuroimaging data. We then iteratively conduct Low-Rank Dimensionality Reduction (LRDR) and orthogonal rotation in a sparse linear regression framework, in order to find the low-dimensional structure of high-dimensional data. Experimental results on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset showed that our proposed model helped enhance the performances of AD classification, outperforming the state-of-the-art methods.
Utilization and safety of proton-pump inhibitors and histamine-2 receptor antagonists in children and adolescents: an observational cohort study
Creators: name: A. Ruigómez
name: S. Johansson
name: P. Nagy
name: L. A. García Rodríguez
Publisher: name: Taylor & Francis
Year: 2018
Subjects: subject: Space Science
subject: Medicine
subject: Pharmacology
subject: Biotechnology
subject: Science Policy
subject: 110309 Infectious Diseases
subject: FOS: Health sciences
subject: Computational Biology

description: Background: Little is known about the use of acid-suppressing treatments and related safety events in children. Objective: This study compared patient characteristics and safety outcomes among children prescribed acid-suppressing drugs for the first time. Methods: The Health Improvement Network was used to determine the characteristics of children prescribed a proton pump inhibitor (PPI; esomeprazole or another PPI) or a histamine-2 receptor antagonist (H2RA) by UK primary care physicians between October 2009 and September 2012. Pre-defined safety outcomes were compared among the treatment groups in up to 18 months of follow-up. Results: The cohorts comprised 8,172 patients on PPIs (including 24 patients on esomeprazole) and 7,905 on H2RAs. The baseline characteristics were similar between cohorts, although the children in the PPI cohorts tended to be older. No safety outcomes occurred in the esomeprazole cohort. In the other-PPIs cohort, 92 safety outcomes occurred, most commonly gastroenteritis (n = 36; 39.1%). In the H2RAs cohort, 193 safety outcomes occurred, most commonly gastroenteritis (n = 62; 32.1%). The incidence of most safety outcomes was higher in the H2RAs cohort than in the other-PPIs cohort, including failure to thrive (3.11 [95% confidence interval (CI) = 2.25–4.28] vs 0.49 per 1,000 person-years [95% CI = 0.22–1.07]) and gastroenteritis (5.27 [95% CI = 4.11–6.75] vs 3.04 per 1,000 person-years [95% CI = 2.20–4.20]). Conclusion: Esomeprazole is rarely prescribed to children when they first require acid-suppressing medication, compared with other PPIs/H2RAs. Overall, more safety outcomes occurred in the H2RAs cohort than in the PPI cohorts.
Managing Financial Risk Trade-Offs for Hydropower Generation Using Snowpack-Based Index Contracts
Creators: name: Reed, Patrick M.
name: Hamilton, Andrew L.
name: Characklis, Gregory W.
Publisher: name: American Geophysical Union (AGU)
Year: 2020

description: Abstract Hydrologic variability poses an important source of financial risk for hydropower-reliant electric utilities, particularly in snow-dominated regions. Drought-related reductions in hydropower production can lead to decreased electricity sales or increased procurement costs to meet firm contractual obligations. This research contributes a methodology for characterizing the trade-offs between cash flows and debt burden for alternative financial risk management portfolios, and applies it to a hydropower producer in the Sierra Nevada mountains (San Francisco Public Utilities Commission). A newly designed financial contract, based on a snow water equivalent depth (SWE) index, provides payouts to hydropower producers in dry years in return for the producers making payments in wet years. This contract, called a capped contract for differences (CFD), is found to significantly reduce cash flow volatility and is considered within a broader risk management portfolio that also includes reserve funds and debt issuance. Our results show that solutions relying primarily on a reserve fund can manage risk at low cost but may require a utility to take on significant debt during severe droughts. More risk-averse utilities with less access to debt should combine a reserve fund with the proposed CFD instrument in order to better manage the financial losses associated with extreme droughts. Our results show that the optimal risk management strategies and resulting outcomes are strongly influenced by the utility's fixed cost burden and by CFD pricing, while interest rates are found to be less important. These results are broadly transferable to hydropower systems in snow-dominated regions facing significant revenue volatility.
Additional file 3 of The different dietary sugars modulate the composition of the gut microbiota in honeybee during overwintering
Creators: name: Wang, Hongfang
name: Liu, Chunlei
name: Liu, Zhenguo
name: Wang, Ying
name: Ma, Lanting
name: Xu, Baohua
Publisher: name: figshare
Year: 2020
Subjects: subject: Microbiology
subject: FOS: Biological sciences

description: Additional file 3: Table S1. Data processing and quality control table.
JPEG2000 Image Compression on Solar EUV Images
Creators: name: Fischer, C. E.
name: Müller, D.
name: De Moortel, I.
Publisher: name: arXiv
Year: 2017
Subjects: subject: Solar and Stellar Astrophysics (astro-ph.SR)
subject: FOS: Physical sciences

description: For future solar missions as well as ground-based telescopes, efficient ways to return and process data have become increasingly important. Solar Orbiter, e.g., which is the next ESA/NASA mission to explore the Sun and the heliosphere, is a deep-space mission, which implies a limited telemetry rate that makes efficient onboard data compression a necessity to achieve the mission science goals. Missions like the Solar Dynamics Observatory (SDO) and future ground-based telescopes such as the Daniel K. Inouye Solar Telescope, on the other hand, face the challenge of making petabyte-sized solar data archives accessible to the solar community. New image compression standards address these challenges by implementing efficient and flexible compression algorithms that can be tailored to user requirements. We analyse solar images from the Atmospheric Imaging Assembly (AIA) instrument onboard SDO to study the effect of lossy JPEG2000 (from the Joint Photographic Experts Group 2000) image compression at different bit rates. To assess the quality of compressed images, we use the mean structural similarity (MSSIM) index as well as the widely used peak signal-to-noise ratio (PSNR) as metrics and compare the two in the context of solar EUV images. In addition, we perform tests to validate the scientific use of the lossily compressed images by analysing examples of an on-disk and off-limb coronal-loop oscillation time-series observed by AIA/SDO.
description: 25 pages, published in Solar Physics
Supplementary Material for: Management of Functional Somatic Syndromes and Bodily Distress
Creators: name: Henningsen, P.
name: Zipfel, S.
name: Sattel, H.
name: Creed, F.
Publisher: name: Karger Publishers
Year: 2018
Subjects: Medicine

description: Functional somatic syndromes (FSS), like irritable bowel syndrome or fibromyalgia and other symptoms reflecting bodily distress, are common in practically all areas of medicine worldwide. Diagnostic and therapeutic approaches to these symptoms and syndromes vary substantially across and within medical specialties from biomedicine to psychiatry. Patients may become frustrated with the lack of effective treatment, doctors may experience these disorders as difficult to treat, and this type of health problem forms an important component of the global burden of disease. This review intends to develop a unifying perspective on the understanding and management of FSS and bodily distress. Firstly, we present the clinical problem and review current concepts for classification. Secondly, we propose an integrated etiological model which encompasses a wide range of biopsychosocial vulnerability and triggering factors and considers consecutive aggravating and maintaining factors. Thirdly, we systematically scrutinize the current evidence base in terms of an umbrella review of systematic reviews from 2007 to 2017 and give recommendations for treatment for all levels of care, concentrating on developments over the last 10 years. We conclude that activating, patient-involving, and centrally acting therapies appear to be more effective than passive ones that primarily act on peripheral physiology, and we recommend stepped care approaches that translate a truly biopsychosocial approach into actual management of the patient.
Methionine restriction-induced sulfur deficiency impairs antitumour immunity partially through gut microbiota
Creators: name: Randall, Tom A.
name: Lu, Kun
name: Shats, Igor
name: Andrea Azcarate-Peril, M.
name: Arbeev, Konstantin G.
name: Ji, Ming
name: Xu, Xin
name: Wu, Xiaoyue
name: Anantharaman, Karthik
name: Wan, Yisong
name: Li, Jian-Liang
name: Li, Xiaoling
name: Yashin, Anatoliy I.
name: Xu, Qing
name: Popov, Vladimir
name: Xu, Xiaojiang
name: Liu, Juan
name: Martin, Cody
name: Ukraintseva, Svetlana
name: Hsiao, Yun-Chung
name: Garcia-Peterson, Liz M.
Publisher: name: Springer Nature
Year: 2023

description: Restriction of methionine (MR), a sulfur-containing essential amino acid, has been reported to repress cancer growth and improve therapeutic responses in several preclinical settings. However, how MR impacts cancer progression in the context of the intact immune system is unknown. Here we report that while inhibiting cancer growth in immunocompromised mice, MR reduces T cell abundance, exacerbates tumour growth and impairs tumour response to immunotherapy in immunocompetent male and female mice. Mechanistically, MR reduces microbial production of hydrogen sulfide, which is critical for immune cell survival/activation. Dietary supplementation of a hydrogen sulfide donor or a precursor, or methionine, stimulates antitumour immunity and suppresses tumour progression. Our findings reveal an unexpected negative interaction between MR, sulfur deficiency and antitumour immunity and further uncover a vital role of gut microbiota in mediating this interaction. Our study suggests that any possible anticancer benefits of MR require careful consideration of both the microbiota and the immune system.
title: ADCO, Septième cartulaire de Saint-Étienne de Dijon (1661-1665), Cart. 29 (G 134), 996 folios, f. 0251
Creators: name: de la Côte d'Or, Archives départementales
name: Petot, Frédéric
name: Archives Départementales De La Côte-D'Or
name: Petot, Frédérique
name: Projet CBMA
name: CG21/F.PETOT/2012
Publisher: name: NAKALA - https://nakala.fr (Huma-Num - CNRS)
publisherIdentifier: https://ror.org/04ces3204
publisherIdentifierScheme: ROR
Year: 2020
Subjects: subject: Laboratoire de Médiévistique Occidentale de Paris
subject: Corpus Burgundiae Medii Aevi
subject: Chartes de la Bourgogne du Moyen Âge
subject: cartulaire
subject: LaMOP

description: Septième cartulaire de Saint-Étienne de Dijon (1661-1665), Archives départementales de la Côte-d'Or, Cart. 29 (G 134), 996 folios, f. 0251, Numérisation en mode image.
description: Relation: http://www.cbma-project.eu/
description: Bibliographic citation: Septième cartulaire de Saint-Étienne de Dijon (1661-1665), Archives départementales de la Côte-d'Or, Cart. 29 (G 134), 996 folios, f. 0251, in Projet CBMA - Corpus Burgundiae Medii Aevi [Ressource en ligne], https://manuscrits.cbma-project.eu/
description: Provenance: http://www.wikidata.org/entity/Q15945019
description: Provenance: abbaye Saint-Étienne de Dijon
Mitigating gyral bias in cortical tractography via asymmetric fiber orientation distributions
Creators: name: Wu, Ye
name: Yap, Pew-Thian
name: Shen, Dinggang
name: Feng, Yuanjing
name: Hong, Yoonmi
Publisher: name: Elsevier
Year: 2019

description: Diffusion tractography in brain connectomics often involves tracing axonal trajectories across gray-white matter boundaries in gyral blades of complex cortical convolutions. To date, gyral bias is observed in most tractography algorithms with streamlines predominantly terminating at gyral crowns instead of sulcal banks. This work demonstrates that asymmetric fiber orientation distribution functions (AFODFs), computed via a multi-tissue global estimation framework, can mitigate the effects of gyral bias, enabling fiber streamlines at gyral blades to make sharper turns into the cortical gray matter. We use ex-vivo data of an adult rhesus macaque and in-vivo data from the Human Connectome Project (HCP) to show that the fiber streamlines given by AFODFs bend more naturally into the cortex than the conventional symmetric FODFs in typical gyral blades. We demonstrate that AFODF tractography improves cortico-cortical connectivity and provides highly consistent outcomes between two different field strengths (3T and 7T).
Supplementary Material for: Benefits of Individualized Feedback in Internet-Based Interventions for Depression: A Randomized Controlled Trial
Creators: name: Zagorscak, P.
name: Heinrich, M.
name: Sommer, D.
name: Wagner, B.
name: Knaevelsrud, C.
Publisher: name: Karger Publishers
Year: 2018
Subjects: Medicine

description: Background: Even though there is an increasing number of studies on the efficacy of Internet-based interventions (IBI) for depression, experimental trials on the benefits of added guidance by clinicians are scarce and inconsistent. This study compared the efficacy of semistandardized feedback provided by psychologists with fully standardized feedback in IBI. Methods: Participants with mild-to-moderate depression (n = 1,089, 66% female) from the client pool of a health insurance company participated in a cognitive-behavioral IBI targeting depression over 6 weeks. Individuals were randomized to weekly semistandardized e-mail feedback from psychologists (individual counseling; IC) or to automated, standardized feedback where a psychologist could be contacted on demand (CoD). The contents and tasks were identical across conditions. The primary outcome was depression; secondary outcomes included anxiety, rumination, and well-being. Outcomes were assessed before and after the intervention and 3, 6, and 12 months later. Changes in outcomes were evaluated using latent change score modeling. Results: Both interventions yielded large pre-post effects on depression (Beck Depression Inventory-II: dIC = 1.53, dCoD = 1.37; Patient Health Questionnaire-9: dIC = 1.20, dCoD = 1.04), as well as significant improvements of all other outcome measures. The effects remained significant after 3, 6, and 12 months. The groups differed with regard to attrition (IC: 17.3%, CoD: 25.8%, p = 0.001). Between-group effects were statistically nonsignificant across outcomes and measurement occasions. Conclusion: Adding semistandardized guidance in IBI for depression did not prove to be more effective than fully standardized feedback on primary and secondary outcomes, but it had positive effects on attrition.
User-friendly introduction to PAC-Bayes bounds
Creators: name: Alquier, Pierre
Publisher: name: arXiv
Year: 2021
Subjects: subject: Machine Learning (stat.ML)
subject: Machine Learning (cs.LG)
subject: Statistics Theory (math.ST)
subject: FOS: Computer and information sciences
subject: FOS: Mathematics

description: Aggregated predictors are obtained by making a set of basic predictors vote according to some weights, that is, to some probability distribution.
 Randomized predictors are obtained by sampling in a set of basic predictors, according to some prescribed probability distribution.
 Thus, aggregated and randomized predictors have in common that they are not defined by a minimization problem, but by a probability distribution on the set of predictors. In statistical learning theory, there is a set of tools designed to understand the generalization ability of such procedures: PAC-Bayesian or PAC-Bayes bounds.
 Since the original PAC-Bayes bounds of D. McAllester, these tools have been considerably improved in many directions (we will for example describe a simplified version of the localization technique of O. Catoni that was missed by the community, and later rediscovered as "mutual information bounds"). Very recently, PAC-Bayes bounds received a considerable attention: for example there was workshop on PAC-Bayes at NIPS 2017, "(Almost) 50 Shades of Bayesian Learning: PAC-Bayesian trends and insights", organized by B. Guedj, F. Bach and P. Germain. One of the reason of this recent success is the successful application of these bounds to neural networks by G. Dziugaite and D. Roy.
 An elementary introduction to PAC-Bayes theory is still missing. This is an attempt to provide such an introduction.
The genesis of indigenous Australian characterisations in feature films
Creators: name: Dennett, Bruce Lawrence
Publisher: name: Macquarie University
Year: 2022
Subjects: Other education not elsewhere classified

description: The media, particularly film, plays a powerful role in the making and unmaking of national identity and identities. In the so-called British settler societies it has often been the first and most significant source of exposure to Indigenous peoples for non-Indigenous audiences. This is particularly so in Australia where the Indigenous population, if not ‘out of sight, out of mind’, has always been on the peripheries except, notably, in film and literature, where Indigenous representations have helped forge particular versions of Australianess. From the first such filmic depiction in 1907 to the most recent in 2009 there has been a continuous re/working of Indigenous character types. Focusing primarily on the silent era of Australian filmmaking (c.1906-1928) this thesis analyses the ways in which Indigenous Australian cinematic characters have been invented and re-invented. But, instead of using Charles Chauvel’s iconic film Jedda (1955) as a starting point for discussion of Indigenous Australian characterisations, as so many film histories in Australia do, I use it as a reference point. Rather than moving forward from Jedda, I go back, exploring the significant history that culminated in Chauvel’s Indigenous characterisations. In doing so I contribute to the scholarship in three ways. The first is by addressing a gap that exists in the literature regarding Indigenous characterisations in the silent era. The second contribution stems from my challenge to the accepted wisdom that typically links Indigenous Australian characterisations with Hollywood’s depiction of Native Americans. I argue that although some of these comparisons are appropriate, blanket comparisons of this kind over-simplify the reality and neglect the ii important contrasts and comparisons to be made between Indigenous Australian and African American characterisations in silent films. Thirdly, I use Jedda as the basis of my typology of Indigenous Australian characters that allows me to investigate the preferred Indigenous Australian cast of characters. That preferred cast includes the Indigenous Australian ‘tracker’ character, the ‘wild’ or ‘tribal black’ and the ‘comic black’. I also add to the scholarship by interrogating why, despite the acknowledged influence of Hollywood, three popular Native American and African American characters – the individualised warrior chieftain, the sexually predatory ‘black buck’ and the romantic heroine – were omitted from the silent Indigenous Australian cast.
Kendrick Poster
Creators: name: Stinckwich, Serge
Publisher: name: figshare
Year: 2018
Subjects: subject: 111706 Epidemiology
subject: FOS: Health sciences
subject: 80110 Simulation and Modelling
subject: FOS: Computer and information sciences

description: Kendrick is a platform for epidemiological modeling and analysis.
Living narrative(s): cinematic corporeality, sonicity and negotiating the cinesomatic experience
Creators: name: Walker, Alison
Publisher: name: Macquarie University
Year: 2022
Subjects: Other education not elsewhere classified

description: This study seeks to translate the cinematic into the cinesomatic through a discussion of cinema sound design. Sound is an ideal starting point to rethink the binary opposition of film and spectator, and to examine sonic storytelling in specifically corporeal terms. It is only in recent decades that film scholarship has begun to address the palpable ‘absence’ of the body in theory. Prior to this, many studies applied psychoanalytic and linguistic frameworks for analysis, which often bypassed the role and position of the body in the creation of meaning. While a large number of scholars have identified this lapse, and developed new paradigms for analysing the body, it is observable that these attempts are still overwhelmingly ocular in their focus. Media scholars such as Vivian Sobchack, Laura Marks and Jennifer Barker, among many others, have drawn on phenomenology to analyse perception and bodily affect within the context of media texts; however, Iargue that this has been overwhelmingly drawn from visual cues. There is considerable scope within the studies of film sound to address this lack. Living Narrative(s) seeks to analyse film sound via the body. Specifically, it asks: what is the relationship between film sound, narrative and the body of the ‘audience’ member? How can we understand the audience’s experience of the filmic narrative as ‘lived’ via the sound design? Can we reframe the experience of sitting in the cinema, and walking away afterwards, as having embodied sonic value? How does film sound consummate the lived experience of self, past and present, with the cinematic narrative? How can we hear, and conceptualise, the resonating intersections between spaces, memories, bodies and amplitudes of intersensory fusion? By conducting an analysis of Gravity (Cuarón, 2013) and Wild (Vallée, 2014) this study seeks to contribute to investigations into sonic cinematic bodily experience, and participate in the theoretical movement towards articulating and validating creative somatic realities.
Molecular control of pathogenic Th17 cells in autoimmune diseases
Creators: name: Wu, Bing
name: Wan, Yisong
Publisher: name: Elsevier
Year: 2020

description: IL-17A-producing CD4+ T helper cells (Th17) are crucial for the development of inflammatory and autoimmune diseases and thus are exploited for clinical immunotherapies. Emerging evidence suggests Th17 cells are heterogeneous and able to adopt both pathogenic and non-pathogenic phenotypes which are shaped by environmental and genetic factors. On one hand, IL-6 in concert with TGFβ1 can induce non-pathogenic Th17 cells (non-pTh17), which are not effective in inducing tissue inflammation. On the other hand, IL-6, IL-1β with IL-23 induce pathogenic Th17 cells (pTh17) to induce immune pathologies in various tissues. Th17 cells could be both pathogenic and non-pathogenic in a content-dependent manner in vivo. Understanding how the generation and pathogenicity of pTh17 cells are regulated will aid us to devise more effective immunotherapy. In this review, we summarize recent advances in the differentiation and regulation of Th17 cells especially pTh17 cells in vitro and in vivo. The emerging results revealing the specific molecular control of pTh17 cells are highlighted.
Mouse Models of Food Allergy in the Pursuit of Novel Treatment Modalities
Creators: name: Smeekens, Johanna M.
name: Kulis, Michael D.
Publisher: name: Frontiers
Year: 2021

description: The prevalence of IgE-mediated food allergies has increased dramatically in the past three decades, now affecting up to 10% of the US population. IgE-mediated food allergy is an immunologic disease, involving a variety of cells, including B and T cells, mast cells, basophils, ILC2s, and epithelial cells. Mouse models of food allergy mimic the overall immunologic processes known to exist in humans. Due to the limitations of invasive sampling of human tissue and the similarities of the human and mouse immune systems, comprehensive pathogenesis studies of food allergy have been performed in mouse models. Mouse models have been effective in elucidating the roles of non-oral routes of sensitization and identifying key cells and molecules involved in allergic sensitization. Furthermore, the development of novel therapeutic approaches for food allergy has been accelerated through the use of pre-clinical mouse models. Despite the groundbreaking findings stemming from research in mice, there are continued efforts to improve the translational utility of these models. Here, we highlight the achievements in understanding food allergy development and efforts to bring novel treatment approaches into clinical trials.
Multi-Channel 3D Deep Feature Learning for Survival Time Prediction of Brain Tumor Patients Using Multi-Modal Neuroimages
Creators: name: Zhang, Han
name: Shen, Dinggang
name: Liu, LuYan
name: Lu, Junfeng
name: Yu, Zhengda
name: Nie, Dong
name: Wang, Jun
name: Wu, Jinsong
name: Adeli, Ehsan
name: Wang, Qian
Publisher: name: Springer Nature
Year: 2019

description: High-grade gliomas are the most aggressive malignant brain tumors. Accurate pre-operative prognosis for this cohort can lead to better treatment planning. Conventional survival prediction based on clinical information is subjective and could be inaccurate. Recent radiomics studies have shown better prognosis by using carefully-engineered image features from magnetic resonance images (MRI). However, feature engineering is usually time consuming, laborious and subjective. Most importantly, the engineered features cannot effectively encode other predictive but implicit information provided by multi-modal neuroimages. We propose a two-stage learning-based method to predict the overall survival (OS) time of high-grade gliomas patient. At the first stage, we adopt deep learning, a recently dominant technique of artificial intelligence, to automatically extract implicit and high-level features from multi-modal, multi-channel preoperative MRI such that the features are competent of predicting survival time. Specifically, we utilize not only contrast-enhanced T1 MRI, but also diffusion tensor imaging (DTI) and resting-state functional MRI (rs-fMRI), for computing multiple metric maps (including various diffusivity metric maps derived from DTI, and also the frequency-specific brain fluctuation amplitude maps and local functional connectivity anisotropy-related metric maps derived from rs-fMRI) from 68 high-grade glioma patients with different survival time. We propose a multi-channel architecture of 3D convolutional neural networks (CNNs) for deep learning upon those metric maps, from which high-level predictive features are extracted for each individual patch of these maps. At the second stage, those deeply learned features along with the pivotal limited demographic and tumor-related features (such as age, tumor size and histological type) are fed into a support vector machine (SVM) to generate the final prediction result (i.e., long or short overall survival time). The experimental results demonstrate that this multi-model, multi-channel deep survival prediction framework achieves an accuracy of 90.66%, outperforming all the competing methods. This study indicates highly demanded effectiveness on prognosis of deep learning technique in neuro-oncological applications for better individualized treatment planning towards precision medicine.
Multi-channel framelet denoising of diffusion-weighted images
Creators: name: Dong, Bin
name: Zhang, Yong
name: Yap, Pew-Thian
name: Shen, Dinggang
name: Zhang, Jian
name: Chen, Geng
Publisher: name: Public Library of Science (PLoS)
Year: 2019

description: Diffusion MRI derives its contrast from MR signal attenuation induced by the movement of water molecules in microstructural environments. Associated with the signal attenuation is the reduction of signal-to-noise ratio (SNR). Methods based on total variation (TV) have shown superior performance in image noise reduction. However, TV denoising can result in stair-casing effects due to the inherent piecewise-constant assumption. In this paper, we propose a tight wavelet frame based approach for edge-preserving denoising of diffusion-weighted (DW) images. Specifically, we employ the unitary extension principle (UEP) to generate frames that are discrete analogues to differential operators of various orders, which will help avoid stair-casing effects. Instead of denoising each DW image separately, we collaboratively denoise groups of DW images acquired with adjacent gradient directions. In addition, we introduce a very efficient method for solving an â„“0 denoising problem that involves only thresholding and solving a trivial inverse problem. We demonstrate the effectiveness of our method qualitatively and quantitatively using synthetic and real data.
Multi-Hypergraph Learning for Incomplete Multimodality Data
Creators: name: Yap, Pew-Thian
name: Liu, Mingxia
name: Gao, Yue
name: Shen, Dinggang
Publisher: name: Institute of Electrical and Electronics Engineers (IEEE)
Year: 2017

description: Multi-modality data convey complementary information that can be used to improve the accuracy of prediction models in disease diagnosis. However, effectively integrating multi-modality data remains a challenging problem, especially when the data are incomplete. For instance, more than half of the subjects in the Alzheimer's disease neuroimaging initiative (ADNI) database have no fluorodeoxyglucose positron emission tomography and cerebrospinal fluid data. Currently, there are two commonly used strategies to handle the problem of incomplete data: 1) discard samples having missing features; and 2) impute those missing values via specific techniques. In the first case, a significant amount of useful information is lost and, in the second case, additional noise and artifacts might be introduced into the data. Also, previous studies generally focus on the pairwise relationships among subjects, without considering their underlying complex (e.g., high-order) relationships. To address these issues, in this paper, we propose a multi-hypergraph learning method for dealing with incomplete multimodality data. Specifically, we first construct multiple hypergraphs to represent the high-order relationships among subjects by dividing them into several groups according to the availability of their data modalities. A hypergraph regularized transductive learning method is then applied to these groups for automatic diagnosis of brain diseases. Extensive evaluation of the proposed method using all subjects in the baseline ADNI database indicates that our method achieves promising results in AD/MCI classification, compared with the state-of-the-art methods.
Multi-Label Nonlinear Matrix Completion With Transductive Multi-Task Feature Selection for Joint MGMT and IDH1 Status Prediction of Patient With High-Grade Gliomas
Creators: name: Wang, Qian
name: Jin, Lei
name: Aibaidula, Abudumijiti
name: Zhang, Han
name: Lu, Junfeng
name: Wu, Jinsong
name: Chen, Lei
name: Chen, Songcan
name: Zhou, Liangfu
name: Thung, Kimhan
name: Liu, Luyan
name: Shen, Dinggang
Publisher: name: Institute of Electrical and Electronics Engineers (IEEE)
Year: 2018

description: The O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation and isocitrate dehydrogenase 1 (IDH1) mutation in high-grade gliomas (HGG) have proven to be the two important molecular indicators associated with better prognosis. Traditionally, the statuses of MGMT and IDH1 are obtained via surgical biopsy, which has limited their wider clinical implementation. Accurate presurgical prediction of their statuses based on preoperative multimodal neuroimaging is of great clinical value for a better treatment plan. Currently, the available data set associated with this study has several challenges, such as small sample size and complex, nonlinear (image) feature-to-(molecular) label relationship. To address these issues, we propose a novel multi-label nonlinear matrix completion (MNMC) model to jointly predict both MGMT and IDH1 statuses in a multi-task framework. Specifically, we first employ a nonlinear random Fourier feature mapping to improve the linear separability of the data, and then use transductive multi-task feature selection (performed in a nonlinearly transformed feature space) to refine the imputed soft labels, thus alleviating the overfitting problem caused by small sample size. We further design an optimization algorithm with a guaranteed convergence ability based on a block prox-linear method to solve the proposed MNMC model. Finally, by using a single-center, multimodal brain imaging and molecular pathology data set of HGG, we derive brain functional and structural connectomics features to jointly predict MGMT and IDH1 statuses. Results demonstrate that our proposed method outperforms the previously widely used single- and multi-task machine learning methods. This paper also shows the promise of utilizing brain connectomics for HGG prognosis in a non-invasive manner.
Theoretical study of the arabinan hydrolysis by an inverting GH43 arabinanase
Creators: name: Jitrayut Jitonnom
name: Supa Hannongbua
Publisher: name: Taylor & Francis
Year: 2018
Subjects: subject: Biophysics
subject: Biochemistry
subject: 29999 Physical Sciences not elsewhere classified
subject: FOS: Physical sciences
subject: Microbiology
subject: FOS: Biological sciences
subject: Biotechnology
subject: 39999 Chemical Sciences not elsewhere classified
subject: FOS: Chemical sciences
subject: 69999 Biological Sciences not elsewhere classified
subject: Inorganic Chemistry
subject: 110309 Infectious Diseases
subject: FOS: Health sciences
subject: Computational Biology

description: The endo-1,5-α-L-arabinanases (ABNases) belong to the glycoside hydrolase family 43 (GH43) and hydrolyse α-1,5-arabinofuranosidic bonds in arabinose-containing polysaccharides by an inverting mechanism. ABNases are key enzymes involved in hemicellulose degradation with various applications in food technology, organic synthesis and biofuel production. Here, the reaction mechanism of the Geobacillus stearothermophilus GH43 ABNases has been investigated using density functional theory method. To probe the role of the pKa modulators (Ser164 and Tyr229) in the reaction, two different orientations of a catalytic acid (Glu201) with respect to the position of these residues are considered. The results show that the orientation involving a hydrogen bond network (Ser164•••Glu201•••Tyr229) is energetically more favourable, compared to the other one (Ser164•••Glu201), with a barrier of 13.6 kcal mol−1, consistent with the experimental data. Our calculations also give support to a single displacement mechanism proposed in the literature where the protonation of glycosidic bond and a nucleophilic attack by a catalytic water occur in a concerted but asynchronous manner.
Multi-Layer Multi-View Classification for Alzheimer's Disease Diagnosis.
Creators: name: Zhang, Changqing
name: Shen, Dinggang
name: Zhou, Tao
name: Chen, Xiaobo
name: Adeli, Ehsan
Publisher: name: Association for the Advancement of Artificial Intelligence (AAAI)
Year: 2018

description: In this paper, we propose a novel multi-view learning method for Alzheimer's Disease (AD) diagnosis, using neuroimaging and genetics data. Generally, there are several major challenges associated with traditional classification methods on multi-source imaging and genetics data. First, the correlation between the extracted imaging features and class labels is generally complex, which often makes the traditional linear models ineffective. Second, medical data may be collected from different sources (i.e., multiple modalities of neuroimaging data, clinical scores or genetics measurements), therefore, how to effectively exploit the complementarity among multiple views is of great importance. In this paper, we propose a Multi-Layer Multi-View Classification (ML-MVC) approach, which regards the multi-view input as the first layer, and constructs a latent representation to explore the complex correlation between the features and class labels. This captures the high-order complementarity among different views, as we exploit the underlying information with a low-rank tensor regularization. Intrinsically, our formulation elegantly explores the nonlinear correlation together with complementarity among different views, and thus improves the accuracy of classification. Finally, the minimization problem is solved by the Alternating Direction Method of Multipliers (ADMM). Experimental results on Alzheimers Disease Neuroimaging Initiative (ADNI) data sets validate the effectiveness of our proposed method.
High-Dimensional Knockoffs Inference for Time Series Data
Creators: name: Chi, Chien-Ming
name: Fan, Yingying
name: Ing, Ching-Kang
name: Lv, Jinchi
Publisher: name: arXiv
Year: 2021
Subjects: subject: Methodology (stat.ME)
subject: Statistics Theory (math.ST)
subject: FOS: Computer and information sciences
subject: FOS: Mathematics
subject: A.0
subject: 62P20, Stats.ML

description: We make some initial attempt to establish the theoretical and methodological foundation for the model-X knockoffs inference for time series data. We suggest the method of time series knockoffs inference (TSKI) by exploiting the ideas of subsampling and e-values to address the difficulty caused by the serial dependence. We also generalize the robust knockoffs inference in Barber, Candès, and Samworth to the time series setting to relax the assumption of known covariate distribution required by model-X knockoffs, since such an assumption is overly stringent for time series data. We establish sufficient conditions under which TSKI achieves the asymptotic false discovery rate (FDR) control. Our technical analysis reveals the effects of serial dependence and unknown covariate distribution on the FDR control. We conduct a power analysis of TSKI using the Lasso coefficient difference knockoff statistic under the generalized linear time series models. The finite-sample performance of TSKI is illustrated with several simulation examples and an economic inflation study.
description: 106 pages, 6 figures
The ideology of Australian poetry anthologies for children
Creators: name: Halliday, Alison
Publisher: name: Macquarie University
Year: 2022
Subjects: Other education not elsewhere classified

description: The poetry anthology is a unique discourse because it is made up of discrete elements. Each of these, the poem, may stand on its own but when placed in the anthology the poems create a text that is more than the sum of its parts. The focus of my thesis is the ideology that is a function of any or all of the poems in an Australian anthology for the implied child reader. The changes in the ideological matrix may be determined for the implied child reader at three different age groups. These are closely allied to particular school stages: (a) preschool or earlier to the end of primary, (b) early secondary school, and (c) the last two years of secondary school. The poetry anthologies for each of these groups reveal changes in the ideology across time and across the different age groups. I argue that there are three dynamic parameters that define the shifts in the fundamental ideologies of the poetry anthology from the youngest reader to the oldest. These are: the movement from the domestic to the societal place, the change from the oral to the written mode, and the shift from the female to the patriarchal orientation. Against these parameters the ideologies of poetry anthologies fall into three main clusters. The first two clusters of ideology are in a relationship of mutual reciprocity. On one hand there are those ideologies that describe the child’s growth to autonomy and personal agency. On the other are those ideologies that reflect the societal shaping of the role of the responsible adult individual within that particular society. The third ideology offers variations of the parameters of poetry itself These are a function of the essential self-reflexive nature of poetry. The core texts are Australian poetry anthologies and in these the framing ideologies may be traced through the changes in subsidiary ideologies such as those concerned with place, national identity and Aboriginality. All the ideologies reflect the metanarratives that shape,and are shaped by, the society which produces and reads the anthology. The poetry anthology is itself both text and context, and the whole reflects the greater contexts of the Australian society in which the poems are written and read.