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Subacromial Motion Metrics for Evaluation of Shoulder Disorders: A Scoping Review
No full textThis is a scoping review that aims to scope the literature for the available evidence on the use of subacromial motion metrics to evaluate shoulder disorders
Calibration Without Failure: Reference Drift in High-Precision Decision Systems
No full textThis registration records the first formal articulation of the conceptual framework Reference Drift, developed within the Meta-Writing Ecology.
The document defines reference drift as a structural governance condition in which a high-precision decision system maintains internal coherence and operational stability while gradually losing alignment with the reference baseline that originally justified its operation.
This version (Version 0.1) is registered as a conceptual and theoretical framework, prior to empirical testing, operationalization, or applied governance design
Clinician Perceptions of Process-Based Therapy Following a Training Video Introduction
No full textProcess-based therapy (PBT) outlines a novel framework for approaching psychotherapy in a way that emphasizes the unique needs and contextual factors of each individual while leveraging existing evidence-based therapeutic techniques. Some theorists are excited by the potential for PBT to propel the field of intervention science forward, and a series of single-subject design studies point to favorable outcomes associated with PBT. However, little research has focused on the dissemination and implementation of PBT thus far, and like any other innovation in intervention science, PBT is vulnerable to joining the research-to-practice gap. Given that clinicians have notable insight regarding their client needs and the practicalities of implementing an innovation, the current study aims to simultaneously disseminate PBT to clinicians using a training video while collecting data about clinicians’ reactions to the video and gather data about clinicians’ reactions to and qualitative feedback about PBT as an intervention following the training and after attempting to implement it for a month. Findings from this study will inform future directions for PBT
Machine Learning–Based Detection of DDoS Attacks in Software-Defined Networks: A PRISMA-Guided Systematic Literature Review
No full textSoftware-Defined Networking (SDN) has emerged as a fundamental architecture for fu
ture Internet systems by enabling centralized control, programmability, and fine-grained
traffic management. However, the logical centralization of the SDN control plane also in
troduces critical vulnerabilities, particularly to Distributed Denial-of-Service (DDoS) at
tacks that can severely disrupt network availability and performance. To address these
challenges, machine learning (ML) techniques have been increasingly adopted to enable
intelligent, adaptive, and data-driven DDoS detection mechanisms within SDN environ
ments. This study presents a PRISMA-guided systematic literature review of recent ML
based approaches for DDoS detection in SDN-based networks. A comprehensive search
of IEEE Xplore, ACM Digital Library, ScienceDirect, and Google Scholar identified 38 pri
mary studies published between 2021 and 2025. The selected studies were systematically
analyzed to examine learning paradigms, experimental environments, evaluation metrics,
datasets, and emerging architectural trends. The synthesis reveals that while single ma
chine learning classifiers remain dominant in literature, hybrid and ensemble-based ap
proaches are increasingly adopted to improve detection robustness under dynamic and
high-volume traffic conditions. Experimental evaluations are predominantly conducted
using SDN emulation platforms such as Mininet integrated with controllers including
Ryu and OpenDayLight, with performance commonly measured using accuracy, preci
sion, recall, and F1-score, alongside emerging system-level metrics such as detection la
tency and controller resource utilization. Public datasets including CICIDS2017,
CICDDoS2019, and InSDN are widely used, although a significant portion of studies rely
on custom SDN-generated datasets to capture control-plane-specific behaviors. Despite
notable advances in detection accuracy, several challenges persist, including limited gen
eralization to low-rate and unknown attacks, dependency on synthetic traffic, and insuf
ficient validation under real-time operational conditions. Based on the synthesized find
ings, this review highlights key research directions toward intelligent, scalable, and resil
ient DDoS defense mechanisms for future Internet architectures, emphasizing adaptive
learning, lightweight deployment, and integration with programmable networking infra
structure
The Experiences of Refugees Accessing and Utilising Palliative Care in High Income Countries – A Scoping Review
No full textThe outcome of this review will be a mapping of current literature of palliative care experiences of refugee and asylum seekers within high income countries. Barriers and facilitators to care will be analysed at micro and meso levels. This will identify gaps in the research and develop areas for future research
Technical White Paper: Planck Yield Metric (PYM) Model
No full textFormalized physical mechanism reconciling 10^120 vacuum tension with k=3 cosmological coupling."This is an updated registration (V2) specifically to include the formalized LaTeX technical proofs and the k=3 mechanical solution for the vacuum energy discrepancy.
A Meta-analysis of the Acoustic Startle Response in Autism Spectrum Disorder
No full textSensory processing differences are nearly universal in Autism, with auditory hyperreactivity and auditory filtering being among the most commonly reported by Autistic individuals. The neural mechanisms underpinning these auditory differences are unclear, and previous research has been mixed. Despite some mixed findings in the literature, meta-analyses revealed broad changes in acoustic processing in Autism compared to their neurotypical peers. Future work is needed to understand the neural differences driving these effects
