cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Hypouricaemic and nephroprotective effects of Poria cocos in hyperuricemic mice by up-regulating ATP-binding cassette super-family G member 2
Creators: name: Liang, Danling
name: Yong, Tianqiao
name: Diao, Xue
name: Chen, Shaodan
name: Chen, Diling
name: Xiao, Chun
name: Zuo, Dan
name: Xie, Yizhen
name: Zhou, Xinxin
name: Hu, Huiping
Publisher: name: Taylor & Francis
Year: 2021
Subjects: subject: Biochemistry
subject: Genetics
subject: FOS: Biological sciences
subject: Pharmacology
subject: Biotechnology
subject: Environmental Sciences not elsewhere classified
subject: Chemical Sciences not elsewhere classified
subject: Biological Sciences not elsewhere classified
subject: Science Policy
subject: Plant Biology

description: Poria coco F.A.Wolf (Polyporaceae) dispels dampness and promotes diuresis implying hypouricaemic action. To examine hypouricaemic action of Poria coco. Ethanol extract (PCE) was prepared by extracting the sclerotium of P. cocos with ethanol, and the water extract (PCW) was produced by bathing the remains with water. PCE and PCW (50, 100 and 200 mg/kg, respectively) were orally administered to hyperuricemic Kunming mice (n = 8) to examine its hypouricaemic effect. Also, molecular docking was performed. P. cocos showed excellent hypouricaemic action, decreasing the serum uric acid of hyperuricaemia (HUA) control (526 ± 112 μmol/L) to 178 ± 53, 153 ± 57 and 151 ± 62 μmol/L (p < 0.01) by PCE and 69 ± 23, 63 ± 15 and 62 ± 20 μmol/L (p < 0.01) by PCW, respectively. According to SCrs, BUNs and H&E staining, PCE and PCW partially attenuated renal dysfunction caused by HUA. They presented no negative effects on ALT, AST and ALP activities. They elevated ABCG2 (ATP-binding cassette super-family G member 2) mRNA and protein expression in comparison to HUA control. In molecular docking, compound 267, 277, 13824, 15730 and 5759 were predicted as the top bioactives of P. cocos against HUA, which even presented better scores than the positive compound, oestrone 3-sulfate. This paper demonstrated the hypouricaemic and nephroprotective effects of P. cocos in hyperuricemic mice by up-regulating ABCG2. These results may be useful for the development of a hypouricaemic agent.
Demo Project 3: DATA set annotation for use in modelling: The DEMO-DATA Project
Creators: name: Baird, Harriet M.
name: West, Robert
name: Webb, Thomas
name: Michie, Susan
name: Hastings, Janna
name: Martin, Sancha
name: Rodger, Amy
Publisher: name: OSF
Year: 2024

description: The DEMO-DATA project will develop and apply a methodology for annotating datasets in
behavioural and social sciences, using data sets used for modelling population trends in
smoking and e-cigarette use as an example.
Pulsed laser sources utilising liquid crystals as intracavity modulators
Creators: name: Wieschendorf, Christoph
Publisher: name: Macquarie University
Year: 2022
Subjects: Other education not elsewhere classified

description: A range of techniques for fabricating optical waveguides in actively doped media has previously been developed. Macquarie University has specialised in the femtosecond laser direct-write technique, a flexible method that enables the inscription of three-dimensional structures into transparent media. By inscribing depressed-cladding waveguides into doped fluoride glass chips, continuous-wave (CW) lasers with extraordinarily large fundamental mode-field diameters have been realised. However, in order to generate optical pulses with high peak-power levels, an actively controlled intracavity loss modulator would be required. While the use of bulk acousto-optic modulators has been demonstrated, the waveguide chip laser architecture is best utilised with a modulator that is compatible with a monolithic and integrated design. In the present work, a novel type of a liquid-crystal based transducer was utilised as an intracavity loss modulator that can be integrated onto the laser chip, opening up the possibility of realising monolithic miniaturised actively Q-switched high peak-power laser sources. This liquid crystal cell was initially developed by our collaborator in the context of distributed sensor networks and therefore its switching behaviour on a microsecond to sub-microsecond timescale had to be studied first. Next, the cell was employed as an active Q-switch in an ytterbium glass waveguide laser, resulting in peak power levels approaching 100 W. Further,the use of this technology in laser chips based on polarisation-maintaining waveguides in crystalline materials was investigated in the visible spectral region, and this approach was also extended towards the mid-infrared spectral region with the aim of utilising nonlinear optical effects in chalcogenide fibres to generate broadband radiation in the important mid-infrared fingerprint region of the optical spectrum. Finally, the feasibility of using the liquid-crystal modulator as a mode-locking device in fibre lasers was investigated and a fibre laser that can be switched between mode-locked, Q-switched and CW operation was demonstrated.
Method of Reduction of Variables for Bilinear Matrix Inequality Problems in System and Control Designs
Creators: name: Chiu, Wei-Yu
Publisher: name: arXiv
Year: 2017
Subjects: subject: Systems and Control (eess.SY)
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: Bilinear matrix inequality (BMI) problems in system and control designs are investigated in this paper. A solution method of reduction of variables (MRVs) is proposed. This method consists of a principle of variable classification, a procedure for problem transformation, and a hybrid algorithm that combines deterministic and stochastic search engines. The classification principle is used to classify the decision variables of a BMI problem into two categories: 1) external and 2) internal variables. Theoretical analysis is performed to show that when the classification principle is applicable, a BMI problem can be transformed into an unconstrained optimization problem that has fewer decision variables. Stochastic search and deterministic search are then applied to determine the decision variables of the unconstrained problem externally and explore the internal problem structure, respectively. The proposed method can address feasibility, single-objective, and multiobjective problems constrained by BMIs in a unified manner. A number of numerical examples in system and control designs are provided to validate the proposed methodology. Simulations show that the MRVs can outperform existing BMI solution methods in most benchmark problems and achieve similar levels of performance in the remaining problems.
description: 16 pages, 2 figures
Exploring diagnosis and imaging biomarkers of Parkinson's disease via iterative canonical correlation analysis based feature selection
Creators: name: Liu, Luyan
name: Adeli, Ehsan
name: Wang, Qian
name: Zhang, Lichi
name: Shen, Dinggang
name: Zhang, Han
Publisher: name: Elsevier
Year: 2018

description: Parkinson's disease (PD) is a neurodegenerative disorder that progressively hampers the brain functions and leads to various movement and non-motor symptoms. However, it is difficult to attain early-stage PD diagnosis based on the subjective judgment of physicians in clinical routines. Therefore, automatic and accurate diagnosis of PD is highly demanded, so that the corresponding treatment can be implemented more appropriately. In this paper, we focus on finding the most discriminative features from different brain regions in PD through T1-weighted MR images, which can help the subsequent PD diagnosis. Specifically, we proposed a novel iterative canonical correlation analysis (ICCA) feature selection method, aiming at exploiting MR images in a more comprehensive manner and fusing features of different types into a common space. To state succinctly, we first extract the feature vectors from the gray matter and the white matter tissues separately, represented as insights of two different anatomical feature spaces for the subject's brain. The ICCA feature selection method aims at iteratively finding the optimal feature subset from two sets of features that have inherent high correlation with each other. In experiments we have conducted thorough investigations on the optimal feature set extracted by our ICCA method. We also demonstrate that using the proposed feature selection method, the PD diagnosis performance is further improved, and also outperforms many state-of-the-art methods.
Supplemental material from The evolution and anatomy of the horse manus with an emphasis on digit reduction
Creators: name: Solounias, Nikos
name: Danowitz, Melinda
name: Stachtiaris, Elizabeth
name: Khurana, Abhilasha
name: Araim, Marwan
name: Sayegh, Marc
name: Natale, Jessica
Publisher: name: The Royal Society
Year: 2018
Subjects: subject: 40308 Palaeontology (incl. Palynology)
subject: FOS: Earth and related environmental sciences

description: Specimen numbers and complete skeletal descriptions of extant and extinct equids
The effects of clinical and non-clinical use of psychedelics on personality traits: A meta-analysis
Creators: name: Puiu, Daria
name: Caggiano, Pietro
name: Laws, Keith
Publisher: name: Open Science Framework
Year: 2022
Subjects: subject: Life Sciences

description: The proposed meta-analysis aims to investigate the effect of psychedelics such as psilocybin, ayahuasca, MDMA and LSD on the Big Five personality traits of agreeableness, openness, neuroticism, conscientiousness and extraversion (Eysenck, 1967). Clinical and non-clinical studies administering personality related outcome measures following psychedelic intake will be included. Studies involving animals and those which do not use personality outcome measures will not be considered.
Individuality in tomb scenes from the Old and Middle Kingdom
Creators: name: Baramilis, Natasha Nicolette
Publisher: name: Macquarie University
Year: 2022
Subjects: Other education not elsewhere classified

description: Although scenes that decorate the walls of tombs are frequently described as typical, many contain features that allow for them to differentiate themselves from one another. Individuality is expressed through the representation of personalised features which often depict specific people who take part in specific events. In some cases, these rare features are immediately obvious and are acknowledged to be distinctive or even unique. Yet, when the minor details of seemingly typical scenes are studied, they too often reveal elements suggesting the phenomena may be more widespread than initially thought. The research conducted for this thesis has been focussed on gathering a substantial corpus of scenes expressing individuality to explore the extent to which tomb scenes may commemorate actual events which occurred during the life of the tomb owner. A diverse range of examples, dating to the Old and Middle Kingdoms, have deliberately been selected from a wide variety of themes for the purpose of discovering the degree to which the scenes in question were present throughout tombs from the period. The thesis produced seeks to contribute to an area that has been understudied, with the aim of drawing attention to the need for ongoing research. It seeks to challenge any interpretation of scenes being dismissed as typical and stresses the importance of examining scenes in greater depth to ascertain the purpose of their inclusion in each tomb and their possible significance to each tomb owner.
New Hierarchies of Derivative nonlinear Schrödinger-Type Equation
Creators: name: Wu, Zhiwei
name: He, Jingsong
Publisher: name: arXiv
Year: 2017
Subjects: subject: Exactly Solvable and Integrable Systems (nlin.SI)
subject: FOS: Physical sciences

description: We generate hierarchies of derivative nonlinear Schrödinger-type equations and their nonlocal extensions from Lie algebra splittings and automorphisms. This provides an algebraic explanation of some known reductions and newly established nonlocal reductions in integrable systems.
Extraction of dynamic functional connectivity from brain grey matter and white matter for MCI classification
Creators: name: Zhang, Lichi
name: Lee, Seong-Whan
name: Chen, Xiaobo
name: Shen, Dinggang
name: Shen, Celina
name: Zhang, Han
Publisher: name: Wiley
Year: 2017

description: Brain functional connectivity (FC) extracted from resting-state fMRI (RS-fMRI) has become a popular approach for diagnosing various neurodegenerative diseases, including Alzheimer's disease (AD) and its prodromal stage, mild cognitive impairment (MCI). Current studies mainly construct the FC networks between grey matter (GM) regions of the brain based on temporal co-variations of the blood oxygenation level-dependent (BOLD) signals, which reflects the synchronized neural activities. However, it was rarely investigated whether the FC detected within the white matter (WM) could provide useful information for diagnosis. Motivated by the recently proposed functional correlation tensors (FCT) computed from RS-fMRI and used to characterize the structured pattern of local FC in the WM, we propose in this article a novel MCI classification method based on the information conveyed by both the FC between the GM regions and that within the WM regions. Specifically, in the WM, the tensor-based metrics (e.g., fractional anisotropy [FA], similar to the metric calculated based on diffusion tensor imaging [DTI]) are first calculated based on the FCT and then summarized along each of the major WM fiber tracts connecting each pair of the brain GM regions. This could capture the functional information in the WM, in a similar network structure as the FC network constructed for the GM, based only on the same RS-fMRI data. Moreover, a sliding window approach is further used to partition the voxel-wise BOLD signal into multiple short overlapping segments. Then, both the FC and FCT between each pair of the brain regions can be calculated based on the BOLD signal segments in the GM and WM, respectively. In such a way, our method can generate dynamic FC and dynamic FCT to better capture functional information in both GM and WM and further integrate them together by using our developed feature extraction, selection, and ensemble learning algorithms. The experimental results verify that the dynamic FCT can provide valuable functional information in the WM; by combining it with the dynamic FC in the GM, the diagnosis accuracy for MCI subjects can be significantly improved even using RS-fMRI data alone.
title: ADCO, Premier cartulaire de l'abbaye de Molesmes (XIIe siècle), Cart. 142 (7 H 6), 128 pages, f. 0065r
Creators: name: de la Côte d'Or, Archives départementales
name: Archives Départementales De La Côte-D'Or
name: Petot, Frédérique
name: Projet CBMA
name: CG21/F.PETOT/2009
name: Petot, Frédéric
Publisher: name: NAKALA - https://nakala.fr (Huma-Num - CNRS)
publisherIdentifier: https://ror.org/04ces3204
publisherIdentifierScheme: ROR
Year: 2020
Subjects: subject: LaMOP
subject: Laboratoire de Médiévistique Occidentale de Paris
subject: cartulaire
subject: Corpus Burgundiae Medii Aevi
subject: Chartes de la Bourgogne du Moyen Âge

description: Premier cartulaire de l'abbaye de Molesmes (XIIe siècle), Archives départementales de la Côte-d'Or, Cart. 142 (7 H 6), 128 pages, f. 0065r, Numérisation en mode image.
description: Relation: http://www.cbma-project.eu/
description: Bibliographic citation: Premier cartulaire de l'abbaye de Molesmes (XIIe siècle), Archives départementales de la Côte-d'Or, Cart. 142 (7 H 6), 128 pages, f. 0065r, in Projet CBMA - Corpus Burgundiae Medii Aevi [Ressource en ligne], https:// manuscrits.cbma-project.eu/
description: Provenance: abbaye de Molesme
description: Provenance: http://www.wikidata.org/entity/Q334044
description: Provenance: https://catalogue.bnf.fr/ark:/12148/cb137389344
EZH2 inhibitor GSK126 suppresses anti-tumor immunity by driving production of myeloid-derived suppressor cells
Creators: name: Huang, Jiani
name: Long, Haixia
name: Zhou, Li
name: Zhu, Bo
name: Wan, Yisong Y
name: Luo, Jing
name: Wang, Zhongyu
name: Zhou, Jie
name: Huang, Shuo
Publisher: name: American Association for Cancer Research (AACR)
Year: 2019

description: Enhancer of zeste homolog (EZH2) is a key epigenetic regulator of gene expression and is frequently overexpressed in various cancer types, suggesting a role in oncogenesis. The therapeutic potential of EZH2 inhibitors is currently being explored, but their effect on antitumor immunity is largely unknown. Here we report that suppressing EZH2 activity using EZH2 inhibitor GSK126 resulted in increased numbers of myeloid-derived suppressor cells (MDSC) and fewer CD4+ and IFNγ+CD8+ T cells, which are involved in antitumor immunity. Addition of a neutralizing antibody against the myeloid differentiation antigen GR-1 or gemcitabine/5-fluorouracil–depleted MDSCs alleviated MDSC-mediated immunosuppression and increased CD4+ and CD8+ T-cell tumor infiltration and GSK126 therapeutic efficacy. Mechanistically, we identified a novel pathway of MDSC production in cancer in which EZH2 inhibition directs myeloid differentiation from primitive hematopoietic progenitor cells. These findings suggest that modulating the tumor immune microenvironment may improve the efficacy of EZH2 inhibitors.
Significance:

This study uncovers a potential mechanism behind disappointing results of a phase I clinical trial of EZH2 inhibitor GSK126 and identifies a translatable combinational strategy to overcome it.
FCN Based Label Correction for Multi-Atlas Guided Organ Segmentation
Creators: name: Shen, Dinggang
name: Shi, Feng
name: Adeli, Ehsan
name: Zhu, Hancan
Publisher: name: Springer Nature
Year: 2020

description: Segmentation of medical images using multiple atlases has recently gained immense attention due to their augmented robustness against variabilities across different subjects. These atlas-based methods typically comprise of three steps: atlas selection, image registration, and finally label fusion. Image registration is one of the core steps in this process, accuracy of which directly affects the final labeling performance. However, due to inter-subject anatomical variations, registration errors are inevitable. The aim of this paper is to develop a deep learning-based confidence estimation method to alleviate the potential effects of registration errors. We first propose a fully convolutional network (FCN) with residual connections to learn the relationship between the image patch pair (i.e., patches from the target subject and the atlas) and the related label confidence patch. With the obtained label confidence patch, we can identify the potential errors in the warped atlas labels and correct them. Then, we use two label fusion methods to fuse the corrected atlas labels. The proposed methods are validated on a publicly available dataset for hippocampus segmentation. Experimental results demonstrate that our proposed methods outperform the state-of-the-art segmentation methods.
Flexible Locally Weighted Penalized Regression With Applications on Prediction of Alzheimer's Disease Neuroimaging Initiative's Clinical Scores
Creators: name: Liu, Yufeng
name: Wang, Peiyao
name: Shen, Dinggang
Publisher: name: Institute of Electrical and Electronics Engineers (IEEE)
Year: 2018

description: In recent years, we have witnessed the explosion of large-scale data in various fields. Classical statistical methodologies, such as linear regression or generalized linear regression, often show inadequate performance on heterogeneous data because the key homogeneity assumption fails. In this paper, we present a flexible framework to handle heterogeneous populations that can be naturally grouped into several ordered subtypes. A local model technique utilizing ordinal class labels during the training stage is proposed. We define a new "progression score" that captures the progression of ordinal classes, and use a truncated Gaussian kernel to construct the weight function in a local regression framework. Furthermore, given the weights, we apply sparse shrinkage on the local fitting to handle high dimensionality. In this way, our local model is able to conduct variable selection on each query point. Numerical studies show the superiority of our proposed method over several existing ones. Our method is also applied to the Alzheimer's Disease Neuroimaging Initiative data to make predictions on the longitudinal clinical scores based on different modalities of baseline brain image features.
Female adherence self-efficacy before and after couple HIV testing and counseling within Malawi's Option B+ program
Creators: name: Hosseinipour, Mina C.
name: Miller, William C.
name: Golin, Carol E.
name: Rosenberg, Nora E.
name: Hoffman, Irving
name: McGrath, Nuala
name: Chimndozi, Limbikani
name: Bhushan, Nivedita
name: Tsidya, Mercy
name: Wesevich, Austin
Publisher: name: Taylor & Francis
Year: 2019

description: Adherence self-efficacy, belief in one’s ability to adhere to daily medication, is strongly associated with antiretroviral therapy (ART) adherence and preventing mother-to-child HIV transmission. Couple-based interventions could enhance self-efficacy and adherence. We assessed the relationship between couple HIV testing and counseling (cHTC) and adherence self-efficacy using a 100-point culturally-adapted adherence self-efficacy scale (ASES). Secondarily, we explored the relationship between ASES and ART adherence. Ninety HIV-positive pregnant women at an antenatal clinic in Lilongwe, Malawi were enrolled in an observational cohort study. They were assessed with ASES immediately before and one month after receiving cHTC. Median ASES scores were 100 (IQR 95, 100) before and 100 (IQR 99, 100) after cHTC; there was a significant median difference (p = 0.02) for participants before and after cHTC. This change in ASES scores was associated with the odds of self-reported ART adherence in the full population (OR 1.1, p = 0.01), and there was a trend in the same direction for participants with imperfect baseline ASES scores (OR 1.1, p = 0.2). In our population, adherence self-efficacy and ART adherence were both quite high, and those who had room to improve in self-efficacy may have benefited from cHTC, which in turn could impact ART adherence and ultimately mother-to-child transmission.
Functional Brain Network Estimation With Time Series Self-Scrubbing
Creators: name: Shen, Dinggang
name: Wang, Zhengxia
name: Li, Weikai
name: Qiao, Lishan
name: Zhang, Limei
Publisher: name: Institute of Electrical and Electronics Engineers (IEEE)
Year: 2019

description: Functional brain network (FBN) is becoming an increasingly important measurement for exploring cerebral mechanisms and mining informative biomarkers that assist diagnosis of some neurodegenerative disorders. Despite its effectiveness to discover valuable hidden patterns in the human brain, the estimated FBNs are often heavily influenced by the quality of the observed data (e.g., blood oxygen level dependent signal series). In practice, a preprocessing pipeline is usually employed for improving data quality. With this in mind, some data points (volumes or time course in the time series) are still not clean enough, due to artifacts including spurious resting-state processes (head movement, mind-wandering). Therefore, not all volumes in the fMRI time series can contribute to the subsequent FBN estimation. To address this issue, we propose a novel FBN estimation method by introducing a latent variable as an indicator of the data quality, and develop an alternating optimization algorithm for jointly scrubbing the data and estimating FBN simultaneously. To further illustrate the effectiveness of the proposed method, we conduct experiments on two public datasets to identify subjects with mild cognitive impairment from normal controls based on the estimated FBNs, and achieve improved accuracies than the baseline methods.
From Stream Flows to Cash Flows: Leveraging Evolutionary Multi-Objective Direct Policy Search to Manage Hydrologic Financial Risks
Creators: name: Hamilton, Andrew L.
name: Characklis, Gregory W.
name: Reed, Patrick M.
Publisher: name: American Geophysical Union (AGU)
Year: 2022

description: Abstract Hydrologic variability can present severe financial challenges for organizations that rely on water for the provision of services, such as water utilities and hydropower producers. While recent decades have seen rapid growth in decision-support innovations aimed at helping utilities manage hydrologic uncertainty for multiple objectives, support for managing the related financial risks remains limited. However, the mathematical similarities between multi-objective reservoir control and financial risk management suggest that the two problems can be approached in a similar manner. This paper demonstrates the utility of Evolutionary Multi-Objective Direct Policy Search for developing adaptive policies for managing the drought-related financial risk faced by a hydropower producer. These policies dynamically balance a portfolio, consisting of snowpack-based financial hedging contracts, cash reserves, and debt, based on evolving system conditions. Performance is quantified based on four conflicting objectives, representing the classic tradeoff between â€œriskâ€ and â€œreturnâ€ in addition to decision-makers' unique preferences toward different risk management instruments. The dynamic policies identified here significantly outperform static management formulations that are more typically employed for financial risk applications in the water resources literature. Additionally, this paper combines visual analytics and information theoretic sensitivity analysis to improve understanding about how different candidate policies achieve their comparative advantages through differences in how they adapt to real-time information. The methodology presented in this paper should be applicable to any organization subject to financial risk stemming from hydrology or other environmental variables (e.g., wind speed, insolation), including electric utilities, water utilities, agricultural producers, and renewable energy developers.
Contributions to mass incarceration: a study on the tough-on-crime policies of the Clinton Administration and their institutional effects
Creators: name: Kidman, Prudence
Publisher: name: Macquarie University
Year: 2022
Subjects: Other education not elsewhere classified

description: Over the past 50 years, the United States has produced an exceptionally punitive criminal justice system resulting in the world’s largest prison population. Attempts to explain its rapid emergence have amassed an extensive and interdisciplinary body of research. Generally speaking, there is presently no determined causal theory of “mass incarceration” phenomena. Nonetheless, institutional frameworks have provided greater insight into the epistemic underpinnings of crime and punishment. Social, historical and economic theories have shown that institutions engender meaning and context which can shape action and ideas and facilitate systematic change accordingly. Analysis of penal policy development from a political institutional perspective is somewhat lacking within such literature. As a result, it will be the framework of this paper. Discursive institutionalism operates under the principle that political institutions are built upon a dynamic force of structure and agency that enable power. Accordingly, ideas and discourse are privileged as explanatory tools because they represent the various contextual nuances of policy development in a holistic way. Utilizing the methodological toolkit of discursive institutionalism, we will undertake a case-study analysis of the discursive processes and outcomes of the Clinton administration approach to crime. Our specific analytical focus will be upon the executive-level politics engaged in during the policy-development stages preceding the passage of the largest, most costly anticrime bill in American history. The Violent Crime Control and Law Enforcement Act of 1994 represented the Democratic Party’s first “tough-on-crime” foray. It was also enacted at a time when crime was in decline. Yet examination of the Clinton administration’s pursuit of punitive criminal justice and mass incarceration outcomes is perceptibly incomplete if not in terms of academic rigour then at least focus. Our intention is to evaluate the material and symbolic consequences of these outcomes in terms of both structure and agency.
Functional MRI registration with tissue-specific patch-based functional correlation tensors
Creators: name: Shen, Dinggang
name: Zhang, Han
name: Cao, Xiaohuan
name: Feng, Qianjin
name: Yang, Ru
name: Yap, Pew-Thian
name: Zhou, Yujia
name: Zhang, Lichi
Publisher: name: Wiley
Year: 2018

description: Population studies of brain function with resting-state functional magnetic resonance imaging (rs-fMRI) rely on accurate intersubject registration of functional areas. This is typically achieved through registration using high-resolution structural images with more spatial details and better tissue contrast. However, accumulating evidence has suggested that such strategy cannot align functional regions well because functional areas are not necessarily consistent with anatomical structures. To alleviate this problem, a number of registration algorithms based directly on rs-fMRI data have been developed, most of which utilize functional connectivity (FC) features for registration. However, most of these methods usually extract functional features only from the thin and highly curved cortical grey matter (GM), posing great challenges to accurate estimation of whole-brain deformation fields. In this article, we demonstrate that additional useful functional features can also be extracted from the whole brain, not restricted to the GM, particularly the white-matter (WM), for improving the overall functional registration. Specifically, we quantify local anisotropic correlation patterns of the blood oxygenation level-dependent (BOLD) signals using tissue-specific patch-based functional correlation tensors (ts-PFCTs) in both GM and WM. Functional registration is then performed by integrating the features from different tissues using the multi-channel large deformation diffeomorphic metric mapping (mLDDMM) algorithm. Experimental results show that our method achieves superior functional registration performance, compared with conventional registration methods.
The gravitational interaction between planets on inclined orbits and protoplanetary disks as the origin of primordial spin--orbit misalignments
Creators: name: Matsakos, Titos
name: Königl, Arieh
Publisher: name: arXiv
Year: 2016
Subjects: subject: Earth and Planetary Astrophysics (astro-ph.EP)
subject: Solar and Stellar Astrophysics (astro-ph.SR)
subject: FOS: Physical sciences

description: Many of the observed spin--orbit alignment properties of exoplanets can be explained in the context of the primordial disk misalignment model, in which an initially aligned protoplanetary disk is torqued by a distant stellar companion on a misaligned orbit, resulting in a precessional motion that can lead to large-amplitude oscillations of the spin--orbit angle. We consider a variant of this model in which the companion is a giant planet with an orbital radius of a few au. Guided by the results of published numerical simulations, we model the dynamical evolution of this system by dividing the disk into inner and outer parts---separated at the location of the planet---that behave as distinct, rigid disks. We show that the planet misaligns the inner disk even as the orientation of the outer disk remains unchanged. In addition to the oscillations induced by the precessional motion, whose amplitude is larger the smaller the initial inner-disk-to-planet mass ratio, the spin--orbit angle also exhibits a secular growth in this case---driven by ongoing mass depletion from the disk---that becomes significant when the inner disk's angular momentum drops below that of the planet. Altogether, these two effects can produce significant misalignment angles for the inner disk, including retrograde configurations. We discuss these results within the framework of the Stranded Hot Jupiter scenario and consider their implications, including to the interpretation of the alignment properties of debris disks.
description: Accepted for publication in AJ
House price and household consumption micro-data approach
Creators: name: Fu, Bowen
Publisher: name: Macquarie University
Year: 2022
Subjects: Other education not elsewhere classified

description: This paper investigates the relationship between house prices and consumption by using the HILDA (Household, Income and Labour Dynamics in Australia) survey over the period of 2003 to 2012. We find young households have the largest changes in consumption in response to changes in house prices. We also find renters (homeowners) have negative (positive) changes in consumption in response to changes in house prices. Under the permanent income hypothesis and the life-cycle model frameworks, these two main findings suggest that the co-movement between house prices and household consumption in Australia may be mainly explained by the credit constraint channel.
Gaussianization of Diffusion MRI Data Using Spatially Adaptive Filtering
Creators: name: Feng, Jun
name: Chen, Geng
name: Liu, Feihong
name: Yap, Pew-Thian
name: Shen, Dinggang
Publisher: name: Elsevier
Year: 2020

description: Diffusion MRI magnitude data, typically Rician or noncentral Ï‡ distributed, is affected by the noise floor, which falsely elevates signal, reduces image contrast, and biases estimation of diffusion parameters. Noise floor can be avoided by extracting real-valued Gaussian-distributed data from complex diffusion-weighted images via phase correction, which is performed by rotating each complex diffusion-weighted image based on its phase so that the actual image content resides in the real part. The imaginary part can then be discarded, leaving only the real part to form a Gaussian-noise image that is not confounded by the noise floor. The effectiveness of phase correction depends on the estimation of the background phase associated with factors such as brain motion, cardiac pulsation, perfusion, and respiration. Most existing smoothing techniques, applied to the real and imaginary images for phase estimation, assume spatially-stationary noise. This assumption does not necessarily hold in real data. In this paper, we introduce an adaptive filtering approach, called multi-kernel filter (MKF), for image smoothing catering to spatially-varying noise. Inspired by the mechanisms of human vision, MKF employs a bilateral filter with spatially-varying kernels. Extensive experiments demonstrate that MKF significantly improves spatial adaptivity and outperforms various state-of-the-art filters in signal Gaussianization.
Stakeholder’s perspectives and experiences of patient and public involvement (PPI) in clinical trials in maternal and neonatal healthcare: protocol for a qualitative evidence synthesis
Creators: name: Smith, Valerie
name: Hannon, Kathleen
name: Eustace-Cook, Jessica
name: Déirdre Daly
Publisher: name: Open Science Framework
Year: 2023
Subjects: subject: Medicine and Health Sciences
subject: Nursing Midwifery
subject: Nursing
subject: FOS: Health sciences
subject: neonatal care
subject: clinical trials
subject: GRIPP2
subject: Patient and public involvement
subject: maternal care
subject: trials methodology

description: This project is a protocol for a qualitative evidence synthesis on stakeholders' (including, but not limited to, trial participants, PPI contributors, and any other member of the trial research team ) experiences and perceptions of Public and Patient Involvement (PPI) in maternal and neonatal clinical trials. ‘Patient and public involvement’ (PPI) refers to conducting research with and/or by patients or members of the public, in opposition to conducting research on these individuals or groups (Staley 2009). References: Staley K. (2009) Exploring Impact: Public involvement in NHS, public health and social care research. INVOLVE, Eastleigh.
Distinct evolutions of Weyl fermion quasiparticles and Fermi arcs with bulk band topology in Weyl semimetals
Creators: name: Xu, N.
name: Autes, G.
name: Matt, C. E.
name: Lv, B. Q.
name: Yao, M. Y.
name: Bisti, F.
name: Strocov, V. N.
name: Gawryluk, D.
name: Pomjakushina, E.
name: Conder, K.
name: Plumb, N. C.
name: Radovic, M.
name: Qian, T.
name: Yazyev, O. V.
name: Mesot, J.
name: Ding, H.
name: Shi, M.
Publisher: name: arXiv
Year: 2017
Subjects: subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: Materials Science (cond-mat.mtrl-sci)
subject: FOS: Physical sciences

description: The Weyl semimetal phase is a recently discovered topological quantum state of matter characterized by the presence of topologically protected degeneracies near the Fermi level. These degeneracies are the source of exotic phenomena, including the realization of chiral Weyl fermions as quasiparticles in the bulk and the formation of Fermi arc states on the surfaces. Here, we demonstrate that these two key signatures show distinct evolutions with the bulk band topology by performing angle-resolved photoemission spectroscopy, supported by first-principle calculations, on transition-metal monophosphides. While Weyl fermion quasiparticles exist only when the chemical potential is located between two saddle points of the Weyl cone features, the Fermi arc states extend in a larger energy scale and are robust across the bulk Lifshitz transitions associated with the recombination of two non-trivial Fermi surfaces enclosing one Weyl point into a single trivial Fermi surface enclosing two Weyl points of opposite chirality. Therefore, in some systems (e.g. NbP), topological Fermi arc states are preserved even if Weyl fermion quasiparticles are absent in the bulk. Our findings not only provide insight into the relationship between the exotic physical phenomena and the intrinsic bulk band topology in Weyl semimetals, but also resolve the apparent puzzle of the different magneto-transport properties observed in TaAs, TaP and NbP, where the Fermi arc states are similar.
description: To appear in Physical Review Letters
Warm unstable asymmetric nuclear matter: critical properties and the density dependence of the symmetry energy
Creators: name: Alam, N.
name: Pais, H.
name: Providência, C.
name: Agrawal, B. K.
Publisher: name: arXiv
Year: 2017
Subjects: subject: Nuclear Theory (nucl-th)
subject: High Energy Astrophysical Phenomena (astro-ph.HE)
subject: Solar and Stellar Astrophysics (astro-ph.SR)
subject: FOS: Physical sciences

description: The spinodal instabilities in hot asymmetric nuclear matter and some important critical parameters derived thereof are studied using six different families of relativistic mean-field (RMF) models. The slopes of the symmetry energy coefficient vary over a wide range within each family. The critical densities and proton fractions are more sensitive to the symmetry energy slope parameter at temperatures much below its critical value ($T_c\sim$14-16 MeV). The spread in the critical proton fraction at a given symmetry energy slope parameter is noticeably larger near $T_c$, indicating that the warm equation of state of asymmetric nuclear matter at sub-saturation densities is not sufficiently constrained. The distillation effects are sensitive to the density dependence of the symmetry energy at low temperatures which tend to wash out with increasing temperature.
description: 13 pages, 10 figures, accepted for publication in Phys. Rev. C
Developing a new variety of kentia palms (Howea forsteriana): up-regulation of cytochrome b561 and chalcone synthase is associated with red colouration of the stems
Creators: name: Herraiz, Alba
name: Stokes, Laura
name: Turnbull, Colin
name: Hutton, Ian
name: Baker, William
name: Savolainen, Vincent
Publisher: name: Taylor & Francis
Year: 2018
Subjects: subject: Biophysics
subject: Biochemistry
subject: Medicine
subject: Molecular Biology
subject: Evolutionary Biology
subject: FOS: Biological sciences
subject: 59999 Environmental Sciences not elsewhere classified
subject: FOS: Earth and related environmental sciences
subject: Ecology
subject: 69999 Biological Sciences not elsewhere classified
subject: Developmental Biology
subject: Science Policy
subject: 110309 Infectious Diseases
subject: FOS: Health sciences
subject: Computational Biology

description: The kentia palm (Howea forsteriana) is endemic to a 12 km2 volcanic island in the Tasman Sea, Lord Howe Island. It is one of the most traded houseplants in the world. The typical kentia palm presents a dark green-coloured stem. Note that the stem is made of leaf rachis and petioles, which are intermingled towards the base. However, we discovered on Lord Howe Island a new biological variety that has a red stem. Red-stemmed palm species are known and highly demanded as decorative plants. However, these red palm horticultural varieties require tropical or subtropical conditions to grow, hence commercialization is limited. Thus, a red-stemmed variety of H. forsteriana may have tremendous market potential. Nonetheless, palm trees grow generally slowly and often reach maturity at 15–20 years old or later, which may make conventional strategies unsuitable for the propagation of a new variety. This difficulty needs to be addressed before commercialization can be achieved. Here, we found that anthocyanin is responsible for the red colouration of the stem in the new variety. Using RNA sequencing and quantitative PCR, we identified two gene isoforms displaying altered expression associated with this red colouration, encoding a cytochrome b561 and a chalcone synthase. The latter protein is known to be part of the anthocyanin biosynthesis pathway, which plays a central role in pigmentation in plants. The levels of cytochrome b561 transcripts accumulated were found to be well correlated with an increased anthocyanin concentration in the red stems.
MicroHECL: High-Efficient Root Cause Localization in Large-Scale Microservice Systems
Creators: name: Liu, Dewei
name: He, Chuan
name: Peng, Xin
name: Lin, Fan
name: Zhang, Chenxi
name: Gong, Shengfang
name: Li, Ziang
name: Ou, Jiayu
name: Wu, Zheshun
Publisher: name: arXiv
Year: 2021
Subjects: subject: Software Engineering (cs.SE)
subject: FOS: Computer and information sciences

description: Availability issues of industrial microservice systems (e.g., drop of successfully placed orders and processed transactions) directly affect the running of the business. These issues are usually caused by various types of service anomalies which propagate along service dependencies. Accurate and high-efficient root cause localization is thus a critical challenge for large-scale industrial microservice systems. Existing approaches use service dependency graph based analysis techniques to automatically locate root causes. However, these approaches are limited due to their inaccurate detection of service anomalies and inefficient traversing of service dependency graph. In this paper, we propose a high-efficient root cause localization approach for availability issues of microservice systems, called MicroHECL. Based on a dynamically constructed service call graph, MicroHECL analyzes possible anomaly propagation chains, and ranks candidate root causes based on correlation analysis. We combine machine learning and statistical methods and design customized models for the detection of different types of service anomalies (i.e., performance, reliability, traffic). To improve the efficiency, we adopt a pruning strategy to eliminate irrelevant service calls in anomaly propagation chain analysis. Experimental studies show that MicroHECL significantly outperforms two state-of-the-art baseline approaches in terms of both accuracy and efficiency. MicroHECL has been used in Alibaba and achieves a top-3 hit ratio of 68% with root cause localization time reduced from 30 minutes to 5 minutes.
Global Sensitivity Analysis of a Coupled Hydro-Economic Model and Groundwater Restriction Assessment
Creators: name: Reed, Patrick M.
name: Rodríguez-Flores, José M.
name: Malek, Keyvan
name: Zeff, Harrison B.
name: Escriva-Bou, Alvar
name: Valero Fandiño, Jorge A.
name: Cole, Spencer A.
name: Karimi, Tina
name: Medellín-Azuara, Josué
Publisher: name: Springer Nature
Year: 2022

description: Assessing impacts on coupled food-water systems that may emerge from water policies, changes in economic drivers and crop productivity requires an understanding of dominant uncertainties. This paper assesses how a candidate groundwater pumping restriction and crop prices, crop yields, surface water price, electricity price, and parametric uncertainties shape economic and groundwater performance metrics from a coupled hydro-economic model (HEM) through a diagnostic global sensitivity analysis (GSA). The HEM used in this study integrates a groundwater depth response, modeled by an Artificial Neural Network (ANN), into a calibrated Positive Mathematical Programming (PMP) agricultural production model. Results show that in addition to a groundwater pumping restriction, performance metrics are highly sensitive to prices and yields of perennial tree crops. These sensitivities become salient during dry years when there is a higher reliance on groundwater. Furthermore, results indicate that performing a GSA for two different water baseline conditions used to calibrate the production model, dry and wet, result in different sensitivity indices magnitudes and factor prioritization. Diagnostic GSA results are used to understand key factors that affect the performance of a groundwater pumping restriction policy. This research is applied to the Wheeler Ridge-Maricopa Water Storage District located in Kern County, California, region reliant on groundwater and vulnerable to surface water shortages.
Shock and Rarefaction Waves in Generalized Hertzian Contact Models
Creators: name: Yasuda, Hiromi
name: Chong, Christopher
name: Yang, Jinkyu
name: Kevrekidis, Panayotis G.
Publisher: name: arXiv
Year: 2016
Subjects: subject: Materials Science (cond-mat.mtrl-sci)
subject: Pattern Formation and Solitons (nlin.PS)
subject: FOS: Physical sciences

description: In the present work motivated by generalized forms of the Hertzian dynamics associated with granular crystals, we consider the possibility of such models to give rise to both shock and rarefaction waves. Depending on the value $p$ of the nonlinearity exponent, we find that both of these possibilities are realizable. We use a quasi-continuum approximation of a generalized inviscid Burgers model in order to predict the solution profile up to times near the shock formation, as well as to estimate when it will occur. Beyond that time threshold, oscillations associated with the discrete nature of the underlying model emerge that cannot be captured by the quasi-continuum approximation. Our analytical characterization of the above features is complemented by systematic numerical computations.
A Complex Solar Coronal Jet with Two Phases
Creators: name: Chen, Jie
name: Su, Jiangtao
name: Deng, Yuanyong
name: Priest, E. R.
Publisher: name: arXiv
Year: 2017
Subjects: subject: Solar and Stellar Astrophysics (astro-ph.SR)
subject: FOS: Physical sciences

description: Jets often occur repeatedly from almost the same location. In this paper, a complex solar jet was observed with two phases to the west of NOAA AR 11513 on July 2nd, 2012. If it had been observed at only moderate resolution, the two phases and their points of origin would have been regarded as identical. However, at high resolution we find the two phases merge into one another and the accompanying footpoint brightenings occur at different locations. The phases originate from different magnetic patches rather than being one phase originating from the same patch. Photospheric line of sight (LOS) magnetograms show that the bases of the two phases lie in two different patches of magnetic flux which decrease in size during the occurrence of the two phases. Based on these observations, we suggest the driving mechanism of the two successive phases is magnetic cancellation of two separate magnetic fragments with an opposite polarity fragment between them.