Digital Commons Network^™

Pyoderma Gangrenosum: An Updated Literature Review On Established And Emerging Pharmacological Treatments, Carlo Alberto Maronese, Matthew A. Pimentel, May M. Li, Giovanni Genovese, Alex G. Ortega-Loayza, Angelo Valerio Marzano

Student Publications

Pyoderma gangrenosum is a rare inflammatory skin disease classified within the group of neutrophilic dermatoses and clinically characterized by painful, rapidly evolving cutaneous ulcers with undermined, irregular, erythematous-violaceous edges. Pyoderma gangrenosum pathogenesis is complex and involves a profound dysregulation of components of both innate and adaptive immunity in genetically predisposed individuals, with the follicular unit increasingly recognized as the putative initial target. T helper 17/T helper 1-skewed inflammation and exaggerated inflammasome activation lead to a dysregulated neutrophil-dominant milieu with high levels of tumor necrosis factor-α, interleukin (IL)-1β, IL-1α, IL-8, IL-12, IL-15, IL-17, IL-23, and IL-36. Low-evidence studies and a lack …

Darboux Transformation And Solitonic Solution To The Coupled Complex Short Pulse Equation, Bao-Feng Feng, Liming Ling

School of Mathematical & Statistical Sciences Faculty Publications

The Darboux transformation (DT) for the coupled complex short pulse (CCSP) equation is constructed through the loop group method. The DT is then utilized to construct various exact solutions including bright soliton, dark-soliton, breather and rogue wave solutions to the CCSP equation. In case of vanishing boundary condition (VBC), we perform the inverse scattering analysis to understand the soliton solution better. Breather and rogue wave solutions are constructed in case of non-vanishing boundary condition (NVBC). Moreover, we conduct a modulational instability (MI) analysis based on the method of squared eigenfunctions, whose result confirms the condition for the existence of rogue …

Definite Condition Of The Evolutionary (P)Over-Right-Arrow(X)-Laplacian Equation, Huashui Zhan, Zhaosheng Feng

School of Mathematical & Statistical Sciences Faculty Publications

For the nonlinear degenerate parabolic equations, how to find an appropriate boundary value condition to ensure the well-posedness of weak solution has been an interesting and challenging problem. In this paper, we develop the general characteristic function method to study the stability of weak solutions based on a partial boundary value condition.

Vaccines And Dermatology: Expanding The Role Of Dermatology Clinics In The Name Of Public Health, Charles Dunn, Yasser Faraj, Nicole Vesely, Michael Foss, Austin Ambur, Rajiv Nathoo

GME Publications

No abstract provided.

Routes To Lower Greenhouse Gas Emissions From Freight Transportation In The City Of San José, Serena Alexander, Kyle Laveroni, Maxwell Friedman, Janani Thiagrajan

Mineta Transportation Institute

Freight represents approximately 30% of all transportation-related emissions in the U.S., but local climate action plans (CAPs) and freight plans often place limited emphasis on freight emissions reduction strategies. The objective of this report is to examine and present strategies for the City of San José, California to reduce GHG emissions from freight. The authors conducted a geospatial analysis of freight data related to San José, and an analysis of relevant literature and successful freight reduction strategies implemented globally. The report also provides key objectives and generalized strategies to reduce GHG emissions from freight as well as specific recommendations for …

Regeneration Time: Ancient Wisdom For Planetary Wellbeing, Anne Poelina, Sandra Wooltorton, Mindy Blaise, Catrina Luz Aniere, Pierre Horwitz, Peta J. White, Stephen Muecke

Research outputs 2022 to 2026

In these regenerative times prompted by the Anthropocene, Aboriginal voices are situated to draw on ancient wisdom for local learning and to share information across the globe as ecological imperative for planetary wellbeing. In this paper, postqualitative research foregrounds the sentient nature of life as ancestral power and brings the vitality of co-becoming as our places into active engagement. It enables coloniality to surface and reveals how it sits in our places and lives, in plain sight but unnoticed because of its so-called common sense. Postqualitative research relates with ancient knowledges in foregrounding Country's animacy and presence, revealing the essence …

Factors Influencing Australian Muslims’ Attitudes Toward Christian-Muslim Dialogue: The Case Of Sunni Muslims Of Adelaide And Uniting Church Christians, Gregory Macdonald, Mohamad Abdalla, Nahid Afrose Kabir

Research outputs 2022 to 2026

Since the implementation of a multicultural policy in the 1970s, religious diversity in Australia has increased. Research has demonstrated that intergroup contact is essential for managing diverse multicultural societies. This is because, given the right conditions, intergroup contact will reduce prejudice and build trust between groups. Given the importance of intergroup contact, policy makers and researchers have identified interfaith dialogue’s importance to the success of multicultural societies. However, there is very limited research that explores interfaith dialogue from the perspectives of adherents, in this case Christians and Muslims in the Australian context. This paper focuses on interfaith dialogue between Christians …

Combined Impacts Of Co2 Enrichment And Water Stress On Growth And Physiology Of Plants Inoculated With An Acc Deaminase Producing Rhizobacterium, Shaijal Babu Ppoyil

Dissertations

This study assessed the water stress mitigating effects of elevated CO₂ on Chloris gayana Kunth cv. Katambora (Rhodes grass) and Medicago sativa L. cv. SuperFast (alfalfa) plants, and how the seed inoculation with one of the ACC deaminase producing plant growth promoting rhizobacterium (PGPR) supplemented the stand-alone plant drought stress mitigating effects of elevated CO₂, under different growing conditions in the United Arab Emirates (UAE). Multiple growth and physiology related variables were measured from the plants in response to different treatment combinations made of CO₂, watering treatments (WT), and PGPR, based on the research design …

Characterization Of The Long Non-Coding Rna Proins In Human Pancreatic Β-Cell, Shareena Saeed Lootah

Dissertations

It is well established that the genome is pervasively transcribed. Only 2% of those transcripts are translated into proteins, and the remaining 98% are non-translated, generating the non-coding RNAs (ncRNAs) species. A close observation of these transcripts directed the scientific community to their increasing potential functional roles in the cells. Indeed, the literature exponentially unveils this notion, with many ncRNAs showing substantial and variable biological functions. The field is in its infancy; however, efforts are accelerating to discover and define this ocean of new species.

Long non-coding RNAs (lncRNAs) are sub-species of ncRNAs with an arbitrary size of more than …

Whole-Genome Sequencing Links Clostridium (Clostridioides) Difficile In A Single Hospital To Diverse Environmental Sources In The Community, Su-Chen Lim, Deirdre Collins, Korakrit Imwattana, Daniel R. Knight, Sicilia Perumalsamy, Natasza M.R. Hain-Saunders, Papanin Putsathit, David Speers, Thomas Riley

Research outputs 2022 to 2026

To investigate if Clostridium (Clostridioides) difficile infection (CDI), traditionally thought of as hospital-acquired, can be genomically linked to hospital or community environmental sources, and to define possible importation routes from the community to the hospital.

In 2019, C. difficile was isolated from 89/300 (29.7%) floor and 96/300 (32.0%) shoe sole samples at a tertiary hospital in Western Australia. Non-toxigenic C. difficile ribotype (RT) 010 predominated among floor (96.6%) and shoe sole (73.2%) isolates, while toxigenic RT 014/020 was most prevalent among contemporaneous clinical cases (33.0%) at the hospital. Whole-genome sequencing and high-resolution core genome single nucleotide polymorphism (cgSNP) …

Efficacy And Safety Of Acupuncture And Or Moxibustion For Managing Primary Dysmenorrhea: A Systematic Review And Meta-Analysis, Weiting Liu, Carol Chunfeng Wang, Khui Hung Lee, Xiaopeng Ma, Timothy Leen Kang

Research outputs 2022 to 2026

Acupuncture and moxibustion have been accepted as add-on options for primary dysmenorrhea (PD); however, the clinical evidence is still inadequate. We searched AMED, CENTRAL, EMBASE, PubMed, Web of Science, CBM, CNKI, VIP, Wangfang database, ANZCTR, ClinicalTrials.gov, and the WHO ICTRP, from their inception to February 2021. The pooled analysis of 13 RCTs with 675 participants for VAS showed that acupuncture and moxibustion were more effective in managing PD than the control group with the MD of −1.93 (95% CI [−2.80, −1.06] and −2.67 (95% CI [−4.96, −0.38]). With the CMSS, seven studies with 487 participants showed that these modalities were …

Human Leucocyte Antigen Genotype Association With The Development Of Immune-Related Adverse Events In Patients With Non-Small Cell Lung Cancer Treated With Single Agent Immunotherapy, Afaf Abed, Ngie Law, Leslie Calapre, Johnny Lo, Vikas Bhat, Samantha Bowyer, Michael Millward, Elin S. Gray

Research outputs 2022 to 2026

Introduction: Biomarkers that predict the risk of immune-mediated adverse events (irAEs) among patients with non-small cell lung cancer (NSCLC) may reduce morbidity and mortality associated with these treatments. Methods: We carried out high resolution human leucocyte antigen (HLA)-I typing on 179 patients with NSCLC treated with anti-program death (PD)-1/program death ligand (PDL)-1. Toxicity data were collected and graded as per common terminology criteria for adverse event (CTCAE) v5.0. We used 14.8-week for landmark analysis to address lead-time bias to investigate the correlation between HLA-I/II zygosity, supertypes and alleles with irAE. Furthermore, we assessed the association for irAE with clinical benefit …

Systemic Perturbations Of The Kynurenine Pathway Precede Progression To Dementia Independently Of Amyloid-Β, Marcela Cespedes, Kelly R. Jacobs, Paul Maruff, Alan Rembach, Christopher J. Fowler, Brett Trounson, Kelly K. Pertile, Rebecca L. Rumble, Stephanie R. Rainey-Smith, Christopher C. Rowe, Victor L. Villemagne, Pierrick Bourgeat, Chai K. Lim, Pratishtha Chatterjee, Ralph N. Martins, Arne Ittner, Colin L. Masters, James D. Doecke, Gilles J. Guillemin, David B. Lovejoy

Research outputs 2022 to 2026

Increasing evidence suggests that kynurenine pathway (KP) dyshomeostasis may promote disease progression in dementia. Studies in Alzheimer's disease (AD) patients confirm KP dyshomeostasis in plasma and cerebrospinal fluid (CSF) which correlates with amyloid-β and tau pathology. Herein, we performed the first comprehensive study assessing baseline levels of KP metabolites in participants enrolling in the Australian Imaging Biomarkers Flagship Study of Aging. Our purpose was to test the hypothesis that changes in KP metabolites may be biomarkers of dementia processes that are largely silent. We used a cross-sectional analytical approach to assess non-progressors (N = 73); cognitively normal (CN) or mild …

‘Even Though You Hate Everything That's Going On, You Know They Are Safer At Home’: The Role Of Aboriginal And Torres Strait Islander Families In Methamphetamine Use Harm Reduction And Their Own Support Needs, Sandra Gendera, Carla Treloar, Rachel Reilly, Katherine M. Conigrave, Julia Butt, Yvette Roe, James Ward

Research outputs 2022 to 2026

Introduction: First Nations people who use methamphetamine are overrepresented in regional and remote Australia and more likely to turn to family for support. This can place strain on families. The support needs of family members of individuals using methamphetamine are poorly understood. Methods: We conducted 19 focus groups and seven interviews with mostly First Nations community, family members and service providers. In total, 147 participants across six sites participated as part of a larger study investigating First Nations perspectives of how to address methamphetamine use and associated harms. We applied a social and emotional wellbeing framework to examine support needs …

Renewable And Recyclable Polymeric Materials For Food Packaging: A New Open Special Issue In Materials, Shima Jafarzadeh, Masoumeh Zargar, Mehrdad Forough

Research outputs 2022 to 2026

“Renewable and Recyclable Polymeric Materials for Food Packaging” is a new open Special Issue of Materials that will publish original and review papers on new scientific and applied research, and the articles it contains will make a contribution to the discovery and understanding of biodegradable and recyclable materials, their functional properties, characterization and applications.

Towards An Optimal Bus Frequency Scheduling: When The Waiting Time Matters, Songsong Mo, Zhifeng Bao, Baihua Zheng, Zhiyong Peng

Research Collection School Of Computing and Information Systems

Reorganizing bus frequencies to cater for actual travel demands can significantly save the cost of the public transport system. This paper studies the bus frequency optimization problem considering the user satisfaction. Specifically, for the first time to our best knowledge, we study how to schedule the buses such that the total number of passengers who could receive their bus services within the waiting time threshold can be maximized. We propose two variants of the problem, FAST and FASTCO, to cater for different application needs and prove that both are NP-hard. To solve FAST effectively and efficiently, we first present an …

Two-Phase Matheuristic For The Vehicle Routing Problem With Reverse Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu

Research Collection School Of Computing and Information Systems

Cross-dockingis a useful concept used by many companies to control the product flow. It enables the transshipment process of products from suppliers to customers. This research thus extends the benefit of cross-docking with reverse logistics, since return process management has become an important field in various businesses. The vehicle routing problem in a distribution network is considered to be an integrated model, namely the vehicle routing problem with reverse cross-docking (VRP-RCD). This study develops a mathematical model to minimize the costs of moving products in a four-level supply chain network that involves suppliers, cross-dock, customers, and outlets. A matheuristic based …

Learning To Solve Multiple-Tsp With Time Window And Rejections Via Deep Reinforcement Learning, Rongkai Zhang, Cong Zhang, Zhiguang Cao, Wen Song, Puay Siew Tan, Jie Zhang, Bihan Wen, Justin Dauwels

Research Collection School Of Computing and Information Systems

We propose a manager-worker framework (the implementation of our model is publically available at: https://github.com/zcaicaros/manager-worker-mtsptwr) based on deep reinforcement learning to tackle a hard yet nontrivial variant of Travelling Salesman Problem (TSP), i.e. multiple-vehicle TSP with time window and rejections (mTSPTWR), where customers who cannot be served before the deadline are subject to rejections. Particularly, in the proposed framework, a manager agent learns to divide mTSPTWR into sub-routing tasks by assigning customers to each vehicle via a Graph Isomorphism Network (GIN) based policy network. A worker agent learns to solve sub-routing tasks by minimizing the cost in terms of both …

Learning Improvement Heuristics For Solving Routing Problems, Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang, Andrew Lim

Research Collection School Of Computing and Information Systems

Recent studies in using deep learning to solve routing problems focus on construction heuristics, the solutions of which are still far from optimality. Improvement heuristics have great potential to narrow this gap by iteratively refining a solution. However, classic improvement heuristics are all guided by hand-crafted rules which may limit their performance. In this paper, we propose a deep reinforcement learning framework to learn the improvement heuristics for routing problems. We design a self-attention based deep architecture as the policy network to guide the selection of next solution. We apply our method to two important routing problems, i.e. travelling salesman …

On The Effectiveness Of Using Graphics Interrupt As A Side Channel For User Behavior Snooping, Haoyu Ma, Jianwen Tian, Debin Gao, Chunfu Jia

Research Collection School Of Computing and Information Systems

Graphics Processing Units (GPUs) are now a key component of many devices and systems, including those in the cloud and data centers, thus are also subject to side-channel attacks. Existing side-channel attacks on GPUs typically leak information from graphics libraries like OpenGL and CUDA, which require creating contentions within the GPU resource space and are being mitigated with software patches. This paper evaluates potential side channels exposed at a lower-level interface between GPUs and CPUs, namely the graphics interrupts. These signals could indicate unique signatures of GPU workload, allowing a spy process to infer the behavior of other processes. We …

An Attribute-Aware Attentive Gcn Model For Attribute Missing In Recommendation, Fan Liu, Zhiyong Cheng, Lei Zhu, Chenghao Liu, Liqiang Nie

Research Collection School Of Computing and Information Systems

As important side information, attributes have been widely exploited in the existing recommender system for better performance. However, in the real-world scenarios, it is common that some attributes of items/users are missing (e.g., some movies miss the genre data). Prior studies usually use a default value (i.e., "other") to represent the missing attribute, resulting in sub-optimal performance. To address this problem, in this paper, we present an attribute-aware attentive graph convolution network (A(2)-GCN). In particular, we first construct a graph, where users, items, and attributes are three types of nodes and their associations are edges. Thereafter, we leverage the graph …

Distance Based Image Classification: A Solution To Generative Classification’S Conundrum?, Wen-Yan Lin, Siying Liu, Bing Tian Dai, Hongdong Li

Research Collection School Of Computing and Information Systems

Most classifiers rely on discriminative boundaries that separate instances of each class from everything else. We argue that discriminative boundaries are counter-intuitive as they define semantics by what-they-are-not; and should be replaced by generative classifiers which define semantics by what-they-are. Unfortunately, generative classifiers are significantly less accurate. This may be caused by the tendency of generative models to focus on easy to model semantic generative factors and ignore non-semantic factors that are important but difficult to model. We propose a new generative model in which semantic factors are accommodated by shell theory’s [25] hierarchical generative process and non-semantic factors by …

Secure Deterministic Wallet And Stealth Address: Key-Insulated And Privacy-Preserving Signature Scheme With Publicly Derived Public Key, Zhen Liu, Guomin Yang, Duncan S. Wong, Khoa Nguyen, Huaxiong Wang, Xiaorong Ke, Yining Liu

Research Collection School Of Computing and Information Systems

Deterministic Wallet (DW) and Stealth Address (SA) mechanisms have been widely adopted in the cryptocurrency community, due to their virtues on functionality and privacy protection, which come from a key derivation mechanism that allows an arbitrary number of derived keys to be generated from a master key. However, these algorithms suffer a vulnerability that, when one derived key is compromised somehow, the damage is not limited to the leaked derived key only, but to the master key and in consequence all derived keys are compromised. In this article, we introduce and formalize a new signature variant, called Key-Insulated and Privacy-Preserving …

Singapore Public Sector Ai Applications Emphasizing Public Engagement: Six Examples, Steven M. Miller

Research Collection School Of Computing and Information Systems

This article provides an overview of six examples of public sector AI applications in Singapore that illustrate different ways of enhancing engagement with the public. These applications demonstrate ways of enhancing engagement with the public by providing greater accessibility to government services (access anywhere, anytime) and speedier responses to public processes and feedback. Some applications make it substantially easier for members of the public to do things or make choices, while others reduce waiting time, either across an entire public infrastructure, or for an individual transaction. Some provide highly individualized coaching to guide a person through the process of doing …

Deep Learning-Based Text Recognition Of Agricultural Regulatory Document, Hua Leong Fwa, Farn Haur Chan

Research Collection School Of Computing and Information Systems

In this study, an OCR system based on deep learning techniques was deployed to digitize scanned agricultural regulatory documents comprising of certificates and labels. Recognition of the certificates and labels is challenging as they are scanned images of the hard copy form and the layout and size of the text as well as the languages vary between the various countries (due to diverse regulatory requirements). We evaluated and compared between various state-of-the-art deep learningbased text detection and recognition model as well as a packaged OCR library – Tesseract. We then adopted a two-stage approach comprising of text detection using Character …

Choice-Based Crowdshipping: A Dynamic Task Display Problem, Alp Arslan, Firat Kilci, Shih-Fen Cheng, Archan Misra

Research Collection School Of Computing and Information Systems

This paper studies the integration of the crowd workforce into a generic last-mile delivery setting in which a set of known delivery requests should be fulfilled at a minimum cost. In this setting, the crowd drivers are able to choose to perform a parcel delivery among the available and displayed requests. We specifically investigate the question: what tasks should be displayed to an individual driver, so as to minimize the overall delivery expenses? In contrast to past approaches, where drivers are either (a) given the choice of a single task chosen so as to optimize the platform’s profit, or (b) …

Secure Hierarchical Deterministic Wallet Supporting Stealth Address, Xin Yin, Zhen Liu, Guomin Yang, Guoxing Chen, Haojin Zhu

Research Collection School Of Computing and Information Systems

Over the past decade, cryptocurrency has been undergoing a rapid development. Digital wallet, as the tool to store and manage the cryptographic keys, is the primary entrance for the public to access cryptocurrency assets. Hierarchical Deterministic Wallet (HDW), proposed in Bitcoin Improvement Proposal 32 (BIP32), has attracted much attention and been widely used in the community, due to its virtues such as easy backup/recovery, convenient cold-address management, and supporting trust-less audits and applications in hierarchical organizations. While HDW allows the wallet owner to generate and manage his keys conveniently, Stealth Address (SA) allows a payer to generate fresh address (i.e., …

Deep Learning For Coverage-Guided Fuzzing: How Far Are We?, Siqi Li, Xiaofei Xie, Yun Lin, Yuekang Li, Ruitao Feng, Xiaohong Li, Weimin Ge, Jin Song Dong

Research Collection School Of Computing and Information Systems

Fuzzing is a widely-used software vulnerability discovery technology, many of which are optimized using coverage-feedback. Recently, some techniques propose to train deep learning (DL) models to predict the branch coverage of an arbitrary input owing to its always-available gradients etc. as a guide. Those techniques have proved their success in improving coverage and discovering bugs under different experimental settings. However, DL models, usually as a magic black-box, are notoriously lack of explanation. Moreover, their performance can be sensitive to the collected runtime coverage information for training, indicating potentially unstable performance. In this work, we conduct a systematic empirical study on …

Contrastive Transformer-Based Multiple Instance Learning For Weakly Supervised Polyp Frame Detection, Tian Yu, Guansong Pang, Fengbei Liu, Yuyuan Liu, Chong Wang, Yuanhong Chen, Johan Verjans, Gustavo Carneiro

Research Collection School Of Computing and Information Systems

Current polyp detection methods from colonoscopy videos use exclusively normal (i.e., healthy) training images, which i) ignore the importance of temporal information in consecutive video frames, and ii) lack knowledge about the polyps. Consequently, they often have high detection errors, especially on challenging polyp cases (e.g., small, flat, or partially visible polyps). In this work, we formulate polyp detection as a weakly-supervised anomaly detection task that uses video-level labelled training data to detect frame-level polyps. In particular, we propose a novel convolutional transformer-based multiple instance learning method designed to identify abnormal frames (i.e., frames with polyps) from anomalous videos (i.e., …

Joint Hyperbolic And Euclidean Geometry Contrastive Graph Neural Networks, Xiaoyu Xu, Guansong Pang, Di Wu, Mingsheng Shang

Research Collection School Of Computing and Information Systems

Graph Neural Networks (GNNs) have demonstrated state-of-the-art performance in a wide variety of analytical tasks. Current GNN approaches focus on learning representations in a Euclidean space, which are effective in capturing non-tree-like structural relations, but they fail to model complex relations in many real-world graphs, such as tree-like hierarchical graph structure. This paper instead proposes to learn representations in both Euclidean and hyperbolic spaces to model these two types of graph geometries. To this end, we introduce a novel approach - Joint hyperbolic and Euclidean geometry contrastive graph neural networks (JointGMC). JointGMC is enforced to learn multiple layer-wise optimal combinations …