Digital Commons Network^™

Neuron Semantic-Guided Test Generation For Deep Neural Networks Fuzzing, Li Huang, Weifeng Sun, Meng Yan, Zhongxin Liu, Yan Lei, David Lo

Research Collection School Of Computing and Information Systems

In recent years, significant progress has been made in testing methods for deep neural networks (DNNs) to ensure their correctness and robustness. Coverage-guided criteria, such as neuron-wise, layer-wise, and path-/trace-wise, have been proposed for DNN fuzzing. However, existing coverage-based criteria encounter performance bottlenecks for several reasons: Testing Adequacy: Partial neural coverage criteria have been observed to achieve full coverage using only a small number of test inputs. In this case, increasing the number of test inputs does not consistently improve the quality of models. Interpretability: The current coverage criteria lack interpretability. Consequently, testers are unable to identify and understand which …

Attribute-Based Encryption With Searchable Encryption, Yang Yang

Research Collection School Of Computing and Information Systems

Attribute-based encryption (ABE) with searchable encryption is a notion that inherits the advantages of both ABE (Goyal et al., 2006) and searchable encryption (SE) (Boneh et al., 2004; Boneh and Waters, 2007) mechanisms to realize secure share and search for the outsourced data. ABE creates fine-grained access control system to prevent sensitive data from being accessed by unauthorized user or external attacker (Bethencourt et al., 2007). SE generates encrypted index for outsourced data such that it can be searched by a keyword trapdoor (or token) (Shi et al., 2007; Naveed et al., 2014), where the outsourced content and search keyword(s) …

Gnnsynergy: A Multi-View Graph Neural Network For Predicting Anti-Cancer Drug Synergy, Zhifeng Hao, Jianming Zhan, Yuan Fang, Min Wu, Ruichu Cai

Research Collection School Of Computing and Information Systems

Drug combinations play very important roles in cancer therapy, as they can enhance curative efficacy and overcome drug resistance. Due to the increasing size of combinatorial space, experimental screening for all the drug combinations becomes infeasible in practice. Therefore, there is a great need to develop accurate computational approaches that can predict potential drug combinations to direct the experimental screening. In this paper, we propose a novel method called GNNSynergy to learn drug embeddings for drug synergy prediction. Given a specific cancer cell line, we propose a multi-view graph neural network framework which considers the current cell line as main …

Double Oracle Neural Architecture Search For Game Theoretic Deep Learning Models, Aye Phyu Phyu Aung, Xinrun Wang, Ruiyu Wang, Hau Chan, Bo An, Xiaoli Li, J. Senthilnath

Research Collection School Of Computing and Information Systems

In this paper, we propose a new approach to train deep learning models using game theory concepts including Generative Adversarial Networks (GANs) and Adversarial Training (AT) where we deploy a double-oracle framework using best response oracles. GAN is essentially a two-player zero-sum game between the generator and the discriminator. The same concept can be applied to AT with attacker and classifier as players. Training these models is challenging as a pure Nash equilibrium may not exist and even finding the mixed Nash equilibrium is difficult as training algorithms for both GAN and AT have a large-scale strategy space. Extending our …

An End-To-End Bi-Objective Approach To Deep Graph Partitioning, Pengcheng Wei, Yuan Fang, Zhihao Wen, Zheng Xiao, Binbin Chen

Research Collection School Of Computing and Information Systems

Graphs are ubiquitous in real-world applications, such as computation graphs and social networks. Partitioning large graphs into smaller, balanced partitions is often essential, with the biobjective graph partitioning problem aiming to minimize both the“cut” across partitions and the imbalance in partition sizes. However, existing heuristic methods face scalability challenges or overlook partition balance, leading to suboptimal results. Recent deep learning approaches, while promising, typically focus only on node-level features and lack a truly end-to-end framework, resulting in limited performance. In this paper, we introduce a novel method based on graph neural networks (GNNs) that leverages multilevel graph features and addresses …

The Effectiveness Of Local Updates For Decentralized Learning Under Data Heterogeneity, Tongle Wu, Zhize Li, Ying Sun

Research Collection School Of Computing and Information Systems

We revisit two fundamental decentralized optimization methods, Decentralized Gradient Tracking (DGT) and Decentralized Gradient Descent (DGD), with multiple local updates. We consider two settings and demonstrate that incorporating local update steps can reduce communication complexity. Specifically, for  $\mu$-strongly convex and $L$-smooth loss functions, we proved that local DGT  achieves communication complexity {}{$\tilde{\mathcal{O}} \Big(\frac{L}{\mu(K+1)} + \frac{\delta + {}{\mu}}{\mu (1 - \rho)} + \frac{\rho }{(1 - \rho)^2} \cdot \frac{L+ \delta}{\mu}\Big)$}, where $K$ is the number of additional local update}, $\rho$ measures the network connectivity and $\delta$ measures the second-order heterogeneity of the local losses. Our results reveal the tradeoff between communication and …

Defending Federated Recommender Systems Against Untargeted Attacks: A Contribution-Aware Robust Aggregation Scheme, Ruicheng Liang, Yuanchun Jiang, Feida Zhu, Ling Cheng, Huiwen Liu

Research Collection School Of Computing and Information Systems

Federated recommender systems (FedRSs) effectively tackle the tradeoff between recommendation accuracy and privacy preservation. However, recent studies have revealed severe vulnerabilities in FedRSs, particularly against untargeted attacks seeking to undermine their overall performance. Defense methods employed in traditional recommender systems are not applicable to FedRSs, and existing robust aggregation schemes for other federated learning-based applications have proven ineffective in FedRSs. Building on the observation that malicious clients contribute negatively to the training process, we design a novel contribution-aware robust aggregation scheme to defend FedRSs against untargeted attacks, named contribution-aware Bayesian knowledge distillation aggregation (ConDA), comprising two key components for the …

Processing Of Verbal Versus Adjectival Agreement: Implications For Syntax And Psycholinguistics, Zuzanna Fuchs, Olga Parshina, Irina A. Sekerina, Maria Polinsky

Publications and Research

Linguistic theories distinguish between external and internal agreement (e.g., noun-verb agreement vs. noun-modifier agreement, the latter also known as concord) and model them using different mechanisms. While this distinction has garnered considerable attention in syntactic theory, it remains largely unexplored in experimental work. In an effort to address this gap, we conducted two studies of external/internal agreement in Russian using self-paced reading and eye-tracking while reading. We measured the response to violations generated when native speakers encounter a noun that mismatches the features on an earlier element inflected for agreement (verb, modifying adjective, and predicative adjective). Both experimental studies found …

The Gender Wage Gap In An Online Labor Market: The Cost Of Interruptions, Abi Adams, Kotaro Hara, Kristy Milland, Chris Callison-Burch

Research Collection School Of Computing and Information Systems

This paper analyses gender differences in working patterns and wages on Amazon Mechanical Turk, a popular online labour platform. Using information on 2 million tasks, we find no gender differences in task selection nor experience. Nonetheless, women earn 20% less per hour on average. Gender differences in working patterns are a significant driver of this wage gap. Women are more likely to interrupt their working time on the platform with consequences for their task completion speed. A follow-up survey shows that the gender differences in working patterns and hourly wages are concentrated amongst workers with children.

Multiple Implant Placements With Simultaneous Soft Tissue Augmentation Using A Volume-Stable Collagen Matrix Compared To Autogenous Connective Tissue Graft: A Clinical And Histological Pilot Study, Jamil Boulos, Abdel-Rahman Kassir, Gabriel Menassa, Nada Naaman

International Arab Journal of Dentistry

Introduction: The use of soft tissue grafts has been a key component in periodontal and implant surgeries for the past five decades, aiming to increase the width of keratinized tissue and soft tissue volume.

Objectives: This study evaluates the efficacy of a three-dimensional volume-stable collagen matrix (VCMX) compared to subepithelial connective tissue grafts (SCTG) in increasing soft tissue thickness and volume during multiple implant placements.

Methods: A randomized controlled clinical trial was conducted with four patients and eight implants. Patients were allocated to the SCTG or VCMX group, with soft tissue augmentation performed simultaneously with implant placement. …

A Two-Stage Radiographic Study Of The Prevalence Of Anomalies Associated With Tooth Number, Vellore Kannan Gopinath, Diaa Elderini, Reem Salama, Sangeetha Narasimhan, Vinayak Kamath, Shishir Shetty

International Arab Journal of Dentistry

Introduction: Dental anomalies (DA) are a group of dental developmental disturbances which appear during tooth formation manifesting themselves as an alteration in tooth number, shape, and size. Dental anomalies of number include hypodontia, mesiodens, supernumerary tooth, and odontoma.

Objectives: To evaluate the prevalence and distribution of dental anomalies associated with tooth number in the radiographic archives of University Dental Hospital Sharjah, United Arab Emirates (UAE).

Methods: Retrospective evaluation of 2000 Orthopantomogram (OPG) images were taken between January 2015 to December 2022. The OPG showing dental anomalies of number were further investigated for the availability of Cone Beam …

The Effect Of Premolar Extractions On The Change Of Angulation And Eruption Space Of The Mandibular Third Molars After Orthodontic Treatment, Asmae Benkaddour, Khaoula M’Rabt, Loubna Bahije, Fatima Zaoui, Asmae Bahoum

International Arab Journal of Dentistry

Objectives: Our study was designed to analyze the effect of lower premolar extraction on the evolution space of the lower third molars, as well as their position and angulation during orthodontic treatment.

Methods: This is a cross-sectional, retrospective, descriptive and analytical study comparing two groups of patients: the first group includes 20 patients treated without premolar extraction, and the second group, 27 patients treated with premolar extraction. Linear and angular measurements were performed on panoramic radiographs and lateral cephalograms of orthodontic pre- and post-treatment.

Results: The eruption space and the horizontal position of the lower third molars, …

Evaluation Of Microtensile Bond Strength Of Composite Under Three Aging Conditions: A Comparative In Vitro Study, Fadi Hammoud, Louis Hardan, Maryse Nassif, Tala El Ghoul, Georges Najjar, Cynthia Kassis

International Arab Journal of Dentistry

Objectives: To investigate the effects of different in-vitro artificial aging protocols on the micro tensile bond strength (µTBS) of composite restorations applied to dentin.

Methods: A total of 88 teeth were prepared on dentin and divided into three distinct aging conditions and a control group : G1) Control group with no aging (n=22); G2) Thermal Cycling (Thermocycling) involving 10,000 cycles between 5°C and 55°C, with a dwell time of 20 seconds (n=22); G3) Mechanical Loading (Cyclic loading) with a 50 N load, a frequency of 1.5 Hz, and 10,000 cycles (n=22); G4) Combined Thermo-mechanical cyclic loading (TMCL) using …

Color Stability Of Conventional, 3d-Printed, And Milled Denture Teeth After Immersion In Coloring Agents: An In Vitro Study, Dany Nassif, Nancy Chemaly, Rim Bourgi, Carole Abi-Ghosn, Louis Hardan, Jihad Fakhouri

International Arab Journal of Dentistry

Objectives: This study investigates the color stability of denture teeth made from different materials when subjected to various staining solutions.

Methods: Forty-five A1 shade upper central incisors were divided into three groups: prefabricated, 3D printed, and milled denture teeth (N=45). Each group was further divided into three subgroups, with teeth immersed in coffee, wine, and artificial saliva for up to 120 days (n=5). ∆E values for color change were measured using an Optishade colorimeter.

Results: The type of teeth, type of solution, and immersion time had a significant effect on color stability (p < 0.001). Interactions between the three variables were all significant (p < 0.001). Conventional denture teeth showed slight color changes with saliva (ΔE = 1.256 by day 120), moderate changes with wine (ΔE = 2.893), and more significant changes with coffee (ΔE = 5.208). Milled denture teeth exhibited no color changes with saliva, noticeable changes with wine (ΔE = 5.359), and moderate changes with coffee (ΔE = 3.137). 3D printed denture teeth showed no color changes with saliva, but increased changes with wine (ΔE = 2.533) and highly significant changes with coffee (ΔE = 10.546). Coffee consistently caused the highest ΔE values, especially in 3D printed teeth.

Conclusions: The study …

Endodontic Management Of Dens Invaginatus Using Dynamic Navigation System In Pediatric Patient: A Case Report, Ayesha Fathima, Sahana Selvaganesh, Ganesh Jeevanandan, Pradeep Solete, Prabahdevi Maganur, Ather Syed Ahmed, Satish Vishwanathaiah

International Arab Journal of Dentistry

Dens invaginatus, also known as dens in dente, is a dental anomaly resulting from infolding the enamel organ into the dental papilla. Dynamic Navigation Systems (DNS) like Navident, offer real-time guidance during endodontic procedures, proving especially useful in complex cases, such as calcified canals or pulp obliteration. This case report presents a 13-year-old female, who reported the chief complaint of continuous pain in the upper left front tooth region. Based on the clinical and radiographical findings, a diagnosis of pulp necrosis and chronic periapical abscess in relation to maxillary canine (23) was established with dens invaginated palatal canal ( Oehler’s …

Oral Lesion As The Initial Presentation In The Diagnosis Of Histiocytosis X: A Case Report With 16-Month Follow-Up, Wassim Al Manhal, Georgio Saad, Charbel Anka, Valerie Aftimos, Michael Daccache, Sophie Abi Raad, Georges Boujaoude

International Arab Journal of Dentistry

Introduction: Langerhans Cell Histiocytosis (LCH) is a rare neoplastic disease that comes from the abnormal proliferation of Langerhans cells (LCs). It presents with a broad clinical spectrum, varying from involvement of a single organ system to multisystem disease, and frequently affects children, although cases in adults have been reported. Oral manifestations of LCH are non-specific and may mimic common periodontal conditions, posing a diagnostic challenge for dental practitioners.

Case Presentation: A 63-year-old female patient presented with complaints of periodontal problems. She was initially diagnosed with periodontitis, but symptoms persisted despite treatment, prompting a referral for further evaluation. Histopathological …

Patient-Related And Tooth-Related Factors As Predictors For Tooth Loss In Periodontitis Patients: A Systematic Review, Cleane Daraze, Carole Chakar, Abdelrahman Kassir, Charbel Anka, Jean-Marie Megarbane

International Arab Journal of Dentistry

Introduction: The treatment of periodontitis aims to prevent further disease progression, to minimize symptoms and perception of the disease, possibly to restore lost tissues and to support patients in maintaining a healthy periodontium. Management of chronic periodontal disease requires a combination of therapeutic modalities and a lifelong commitment to periodontal self-care.

Objectives: The aim of this study is to evaluate predictors for tooth loss in patients previously diagnosed with periodontitis. This systematic review covers studies of over 10 years of follow up.

Methods: Electronic literature search was conducted on 19/02/2024 by one author across several databases, including …

Comparative Evaluation Of Marginal And Internal Fit Of Zirconia Crown Designed Using Artificial Intelligence And Cad-Cam Software: A Systematic Review, Pritesh Gangde, Sweta Kale Pisulkar, Arushi Beri, Pritam Das

International Arab Journal of Dentistry

Introduction: The long-term performance of dental restorations depends on their internal and marginal fits. Improvements in the fit of restorations, especially zirconia crowns, have been investigated through the use of diverse materials, manufacturing processes, and impression techniques.

Objectives: The purpose of this review was to examine the internal and marginal fit of zirconia crowns made with CAD/CAM software with artificial intelligence (AI) software.

Methods: Using a combination of keywords and MeSH terms, the literature search was carried out across seven databases: PubMed, Scopus, Web of Science, Cochrane Library, Embase, ProQuest, and ScienceDirect from inception till 1st of …

Genai’S Impact On Global It Management: A Multi-Expert Perspective And Research Agenda, Yogesh K. Dwivedi, Laurie Hughes, Mohammad S. Al-Ahmadi, Vincent Dutot, Syed Q. Ahmed, Shahriar Akter, Rahul De’, Keyao Li, Nitish Singh, Paul Walton

Research outputs 2022 to 2026

Generative AI (GenAI) is disrupting global IT management and challenging established practice. The increasing use of GenAI technology is redefining localization, transforming existing workforce roles, outsourcing strategy, and team dynamics. Simultaneously, GenAI’s security complexities have prompted the rethinking of existing risk frameworks to meet a new set of challenges from GenAI enhanced cyber threats. This article explores these complex and converging factors, providing a roadmap to address GenAI’s significant impact on global IT management. We advocate the responsible adoption of GenAI and importance of building resilient, value-driven, globally consistent IT ecosystems able to adapt to the significant challenges and opportunities …

A Hopeful Or Hopeless Future? Perspectives On The Challenges And Opportunities In Catholic Education, Christine Robinson, Linda Cranley

Research outputs 2022 to 2026

The research presented in this paper offers a significant contribution to existing discourse that explores the challenges and opportunities within Catholic education. In an increasingly secularised world, Catholic education continues its mission to form and inform young people in the faith. The Church acknowledges that the Catholic school enacts the mission of the Church in society and does so despite a detraditionalised cultural context. The Global Researchers Advancing Catholic Education, known as G.R.A.C.E, was formed to act as a global network of Catholic educators to respond to the ‘signs of the times’ in an innovative and integrated way. This paper …

Ability Grouping In Primary Physical Education In England: Moving Beyond Binary Discourses And Practices, Shaun D. Wilkinson, Dawn Penney

Research outputs 2022 to 2026

This study recognised that there is currently limited understanding of the extent and nature of ability grouping practices in subject areas other than mathematics and English in primary schools. Using survey methods, this research sought to generate data of sufficient scale to extend understanding of the use of ability grouping practices in primary physical education (PE) in England. Administration of a web-based survey to all (n = 917) state-funded mainstream and special schools catering for students in Key Stage 1 (aged 5–7) and/or Key Stage 2 (aged 7–11) in the North East of England produced a response rate of 27.7% …

Automated Abdominal Aortic Calcification Scoring From Vertebral Fracture Assessment Images And Fall-Associated Hospitalisations: The Manitoba Bone Mineral Density Registry, Marc Sim, Abadi K. Gebre, Jack Dalla Via, Siobhan Reid, Mohammad Jafari Jozani, Douglas Kimelman, Barret A. Monchka, Syed Zulqarnain Gilani, Zaid Ilyas, Cassandra Smith, David Suter, John T. Schousboe, Joshua R. Lewis, William D. Leslie

Research outputs 2022 to 2026

Abdominal aortic calcification (AAC), a subclinical measure of cardiovascular disease (CVD) that can be assessed on vertebral fracture assessment (VFA) images during osteoporosis screening, is reported to be a falls risk factor. A limitation to incorporating AAC clinically is that its scoring requires trained experts and is time-consuming. We examined if our machine learning (ML) algorithm for AAC (ML-AAC24) is associated with a higher fall-associated hospitalisation risk in the Manitoba Bone Mineral Density (BMD) Registry. A total of 8565 individuals (94.0% female, age 75.7 ± 6.8 years) who had a BMD and VFA image from DXA between February 2010 and …

Bone Mineral Density In Childhood Cancer Survivors During And After Oncological Treatment: A Systematic Review And Meta-Analysis, Anna Maria Markarian, Dennis R. Taaffe, Francesco Bettariga, Hao Luo, Daniel A. Galvão, Jodie Cochrane Wilkie, Carolyn J. Peddle-Mcintyre, Robert U. Newton

Research outputs 2022 to 2026

Osteoporosis poses a significant concern for childhood cancer survivors (CCS). While recommendations for surveillance and management of bone mineral density (BMD) exist, no systematic review and meta-analysis has been undertaken to quantify BMD Z-scores in childhood cancer patients undergoing cancer treatment and survivors who have completed treatments. Accordingly, we conducted a systematic review with a 3-level mixed-effects meta-analysis to examine the course of BMD Z-scores in childhood cancer patients and survivors and identified possible moderators using meta-regression models. A systematic search was conducted in CINAHL, Embase, PubMed, SPORTDiscus, and Web of Science databases from inception to November 2023. We included …

Design Of An Improved Robust Fractional-Order Pid Controller For Buck–Boost Converter Using Snake Optimization Algorithm, Seyyed Morteza Ghamari, Hasan Molaee, Mehrdad Ghahramani, Daryoush Habibi, Asma Aziz

Research outputs 2022 to 2026

With the increasing complexity of modern power systems, effective control of DC–DC converters has become crucial to ensure stability and efficiency. This paper focuses on optimizing the parameters of a known fractional-order proportional–integral–derivative (FOPID) controller for the control of a DC–DC buck–boost converter. The control of a DC–DC buck–boost converter is achieved using aFOPID approach. The gains of this technique have been enhanced utilizing the snake optimization (SO) algorithm. This converter exhibits unfavourable behaviour due to its non-minimum structure, necessitating a well-regulated controller to guarantee stability. The fractional concept is suggested here to enhance the dynamics of the classical PID …

Does Capital Structure Mediate The Relationship Between Corporate Governance Compliance And Firm Performance? Empirical Evidence From Pakistan, Irfan Haider Shakri, Jaime Yong, Erwei Xiang

Research outputs 2022 to 2026

Purpose: The purpose of this study is to examine how capital structure mediates the effects of corporate governance (CG) compliance on firm performance (FP) in the context of a developing market experiencing significant reforms to its governance landscape. Design/methodology/approach: An index was built to measure firm-level compliance with Pakistan’s code of CG. Several robustness checks were performed, including alternate proxies of dependent and independent variables, using additional control variables and considering the Global Financial Crisis period. To address dynamic effects and endogeneity, several identification strategies were used: a leading dependent variable, fixed effects model, generalised method of moments model and …

Investigating The Interplay Of Thermal, Lighting, And Acoustics In Intensive Care For Enhanced Patient Well-Being And Clinical Outcomes, Emil E. Jonescu, Edward Litton, Benjamin Farrell

Research outputs 2022 to 2026

This research explores the interplay among noise levels, thermal conditions, and lighting intensity in an intensive care unit (ICU), focusing on preserving circadian rhythm and promoting nighttime sleep to advance patient-centric care. This investigation assesses lighting levels (Lux), natural versus artificial light ratios, ICU room temperature, and correlations with acoustic data during a field research period and examines the collective impact of patient exposure to sleep linked to delirium and health outcomes, addressing critical gaps in understanding. Findings reveal that noise levels between 60 and 90 dB(A) during patient occupancy exceed sleep disruption thresholds, with daytime averages of 53.6 dB(A) …

Kaartdijin Bidi (Learning Journey): Place-Based Cultural Regeneration At University, Sandra Wooltorton, Lauren Stephenson, Kathie Ardzejewska, Len Collard

Research outputs 2022 to 2026

Imagine being in a university that functions in a place-based culturally regenerative way. In this concept paper, the authors bring together theory, practice, and experience, in the service of transforming universities towards place-based cultural regeneration. At present, Australian universities operate using an economic philosophy of neoliberal corporatism characterised by hierarchical management strategies, competitive tendencies, patriarchal values, and discourse characterised by bifurcation or binary thinking. These features illustrate a worldview that is entangled with the meta crises of our times such as climate change, species loss, hatred/intolerance, and unfathomable violence. The authors consider ways of moving towards a place-based, Indigenous-informed, practical, …

Molecular Testing Of Lung Cancer In Australia: Consensus Best Practice Recommendations From The Royal College Of Pathologists Of Australasia In Collaboration With The Thoracic Oncology Group Of Australasia, Wendy A. Cooper, Benhur Amanuel, Caroline Cooper, Stephen B. Fox, Jon W.A. Graftdyk, Peter Jessup, Sonja Klebe, Wei Sen Lam, Trishe Y.M. Leong, Zarnie Lwin, Rachel Roberts-Thomson, Benjamin J. Solomon, Rebecca Y. Tay, Rebecca Trowman, Janney L. Wale, Nick Pavlakis

Research outputs 2022 to 2026

Molecular testing plays a critical role in guiding optimal treatment decisions for lung cancer patients across a variety of clinical settings. While guidelines for biomarker testing exist in other jurisdictions, to date no best practice guidelines have been developed for the Australian setting. To address this need, the Royal College of Pathologists of Australasia collaborated with the Thoracic Oncology Group of Australasia to identify state-based pathologists, oncologists and consumer representatives to develop consensus best practice recommendations. Sixteen recommendations were established encompassing appropriate biomarkers, lung cancer subtype, tumour stage, specimen types, assay selection and quality assurance protocols that can inform and …

More Than One Way To Be A Planktivore: The Vast Morphospace Of Plankton-Feeding Reef Fishes, Isabelle Ng, David R. Bellwood, Jan M. Strugnell, Sergio R. Floeter, Alexandre C. Siqueira

Research outputs 2022 to 2026

Planktivorous reef fishes are thought to possess unique morphological traits to feed on small, evasive prey. Despite the multitude of family-level studies addressing this hypothesis, results remain inconclusive. Our goal, therefore, was to determine whether specialised traits and patterns of morphological convergence are congruent across a comprehensive phylogeny of reef-associated fishes. We measured 15 morphological traits from 815 images of 299 species in 12 globally distributed families. Using phylogenetic comparative methods, we mapped the evolution of plankton-feeding across lineages; assessed the effect of planktivory on body shape; and tested for the presence of morphological convergence among planktivores. We demonstrate that …

Prevalence And Profile Of New Zealand Osteopaths Treating People Experiencing Headaches And Migraines, Ana Paula Antunes Ferreira, Brett Vaughan, Jerry Draper-Rodi, Lee Muddle, Loïc Treffel, Cindy Mcintyre, Michael Fleischmann, Francesco Cerritelli, Kesava Kovanur Sampath, Amie Steel

Research outputs 2022 to 2026

To describe the prevalence and profile of NZ osteopaths treating people experiencing headaches and migraines. This study is the first to describe this practice. Manual and manipulative therapy interventions are commonly sought by individuals experiencing headaches or migraines. Evidence supports the use of manual therapy as part of the management of headache and migraine disorders. Osteopaths are health professionals who provide care for individuals experiencing headaches and migraines. However, there is a lack of data concerning the profile of osteopaths treating these conditions, in addition to their diagnostic and management strategies. The Osteopathy Research Connect-New Zealand (ORC-NZ), a practice-based research …