Digital Commons Network^™

Clinical Performance Of Heart Failure Palliative Care Referral Criteria: A Retrospective Study, Yi-Wen Chen, Chia Chun Tang, Hsien-Liang Huang, Jui-Yi Chen, Pei-Yi Wang, Shan-Ting Chen, Ching-Yi Lee

International Nursing Research Congress (INRC)

Background: Heart failure (HF) carries a high symptom burden and mortality (Fernandes Pedro & Reis-Pina, 2022). Despite guideline support for early palliative care (PC), referral remains low. The Chang et al., 2022 criteria were developed to enable rapid (Chang et al., 2022), nurse-led screening of patients with advanced HF, but their clinical performance is unclear. This study examined PC referral patterns among hospitalized HF patients and evaluated the diagnostic accuracy and agreement of these criteria.

Methods: We conducted a retrospective case–control study using 2023–2024 electronic medical records from a tertiary hospital. Adults admitted with a principal diagnosis of HF were …

Informing The In-Water Humpback Whale (Megaptera Novaeangliae) Interaction Management Program In The Ningaloo Marine Park, Western Australia, Julian A. Tyne, Holly Raudino, Lyn Irvine, Chandra Salgado Kent, Kelly Waples

Research outputs 2022 to 2026

Introduction: Whale and dolphin watching tourism continues to expand globally, generating substantial economic benefits for coastal communities. However, ensuring that tourism activities remain safe, sustainable, and do not adversely affect cetacean populations remains a significant management challenge. This study evaluated humpback whale (Megaptera novaeangliae) distribution in relation to the intensity of commercial in-water interactions at the commencement of a tourism program off Ningaloo Marine Park (NMP), Western Australia.

Methods: Aerial surveys were conducted in 2016, 2017, and annually from 2022 to 2024 to assess humpback whale distribution and abundance, while vessel-based Electronic Monitoring System data were used to quantify commercial …

Draft Final 2023 Reclamation Improvement Sites Sampling: Bres No. 31 – Waste Dump #5 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

This Butte Priority Soils Operable Unit (BPSOU) Reclamation Improvement (RI) Site Evaluation Summary Report (SESR) presents results of soil sampling conducted on October 16, 2023, at the Butte Reclamation Evaluation System (BRES) No. 31 – Waste Dump #5 Site and adjacent areas (referred to herein as Site) within the BPSOU. The BPSOU Consent Decree (CD) (referred to herein as BPSOU CD; EPA, 2020) Appendix D, Attachment C Further Remedial Elements Scope of Work (FRESOW) prescribed further evaluation of sites reclaimed prior to establishment of the Butte Hill Revegetation Specifications (BHRS) (Appendix A to the BPSOU CD), which were initially established …

Back Cover, Michaela Velleno, Zoé Shaikh

.RAW Journal of Art and Design

No abstract provided.

Credits, Michaela Velleno, Zoé Shaikh

.RAW Journal of Art and Design

No abstract provided.

Artist Index, Owen Isachsen

.RAW Journal of Art and Design

No abstract provided.

'Reclamation', Ainsley Gavin

.RAW Journal of Art and Design

No abstract provided.

'Market Research', Maneli Mianji

.RAW Journal of Art and Design

No abstract provided.

'Chalawan', Jolina Chen

.RAW Journal of Art and Design

No abstract provided.

'Pawpstarz Photocards' & 'Idolize', Erin Robinson, Zoé Shaikh

.RAW Journal of Art and Design

No abstract provided.

'Catch Of The Day' & 'Benediction', Addy Cota, Lillie Turinsky

.RAW Journal of Art and Design

No abstract provided.

'Shanwu 善舞' & 'Scream Queen', Gabrielle Yu, Kyra Oh

.RAW Journal of Art and Design

No abstract provided.

'Warmth And Fluidity'; 'My Best Friend'; & 'Epiphany', Lucky Rodriguez, Sierra Hall, Connor Larson

.RAW Journal of Art and Design

No abstract provided.

'Pop!' & 'Cherries', Alyssa Shavely, Gillian Grow-Juarez

.RAW Journal of Art and Design

No abstract provided.

'Drag'; 'Obsession Rewritten'; & 'Untitled', Maxwell Rice, Mia Haney, Cézar Gomez

.RAW Journal of Art and Design

No abstract provided.

'Swell Sisters', Sophia Tiemens

.RAW Journal of Art and Design

No abstract provided.

'Love Forever And Forever In Love', Tracy Jackson

.RAW Journal of Art and Design

No abstract provided.

'4 Legged Creatures Discover The Sun' & 'Interim', Moussa Ndiaye, Joshua Mahlow

.RAW Journal of Art and Design

No abstract provided.

'Cut Plane Sand' & 'Spring Break', Luke Gillon, Jaiden Duffee

.RAW Journal of Art and Design

No abstract provided.

'Nourish Nymphs', María Belén Luzuriaga Abad

.RAW Journal of Art and Design

No abstract provided.

'Fish 1, Fish 2' & 'The Reef', Yagmur Wernimont, Victoria Dai

.RAW Journal of Art and Design

No abstract provided.

Preface, Sophia Tiemens

.RAW Journal of Art and Design

No abstract provided.

Table Of Contents, Sierra Hall

.RAW Journal of Art and Design

No abstract provided.

Opening, Michaela Velleno, Zoé Shaikh

.RAW Journal of Art and Design

No abstract provided.

Cover, Owen Isachsen

.RAW Journal of Art and Design

No abstract provided.

Full Issue, Michaela Velleno, Zoé Shaikh

.RAW Journal of Art and Design

No abstract provided.

Lightweight Open Source On-Spacecraft Machine Learning With Mlpack And F Prime, Ryan R. Curtin, Scott M. Gilliland, Sterling L. Peet

Small Satellite Conference

Onboard machine learning is an increasingly important topic in spaceflight systems, as machine learning and AI models are increasingly used for data processing, anomaly detection, attitude control systems, and other predictive applications. However, successfully deploying a machine learning model in a spaceflight computing environment is fraught with difficulty, as spaceflight computing environments are low-resource, but typical machine learning software solutions are implemented in languages like Python, which require an interpreter and other heavyweight dependencies. It is therefore virtually mandatory for any on-spacecraft machine learning to be written with lightweight toolkits that minimize dependencies and resource usage.

We demonstrate a solution …

A Novel Deployable Telescope For Small Satellites Using Adaptive Optic Technology, William Hill, Harbinder Rana, Darren Jones, Trevor Wood, Zac Thomas, Thomas Lacy, Duncan Housden, Calum Meredith

Small Satellite Conference

SSTL has been developing a deployable telescope with funding from the UK Defence and Security Accelerator (DASA). The aim of the study was to design a telescope that could achieve higher resolutions in the visible spectrum while utilising a smaller launch volume. To achieve a cost-effective launch the deployable system has been sized such that it would fit within a representative SSTL platform in a SpaceX Falcon 9 small satellite launch volume. A monolithic system with equivalent performance would require a larger launch volume and, therefore, it is expected that a deployable telescope can secure an overall mission price advantage. …

Scaling Up Monolithic Optics Capabilities: 25cm Aperture And Beyond, Cohl Houldin Hatala, Jordan Smilo, Wim De Vries, Brian Bauman, Christian Tolfa, John Cortes, Paul Rosso, Aaron Godfrey, Darrell Carter, Michael Wong, Seth Cornman, Josephine Smith, John Ganino, Ben Bahney

Small Satellite Conference

The 25 cm “V10” Monolithic Optical Payload has been developed through study phase design into a fully qualified system ready for on-orbit demonstration. This extends Lawrence Livermore National Laboratory’s monolithic telescope technology toward a rapidly fieldable, high performance space imaging system for small and medium spacecraft buses. Centered on the V10 monolithic Cassegrain optic in fused silica, the payload provides highly robust, diffraction limited performance with inherently maintained mirror alignment, eliminating complex on orbit alignment procedures and significantly reducing mechanical risk. The V10 optic is paired with a heritage focus mechanism and a panchromatic commercial off the shelf CMOS detectors, …

Payload Operation Using On-Board Vision Language Model, Meirav Nevo, Oshri Fatkiev, Guy Zaidman, Doron Shterman

Small Satellite Conference

The rapid maturation of multimodal vision-language models (VLMs) has significantly expanded artificial intelligence applications at the edge, including spaceborne systems. In this work, we present one of the first demonstrations of deploying a compact vision-language model directly on a very-high-resolution Earth-observation satellite payload processor, enabling autonomous on-orbit scene understanding and near real-time decision-making. This represents a paradigm shift in satellite operations, moving from ground-centric processing toward intelligent, self-directed spacecraft. 

Conventional Earth-observation missions rely on ground-based image processing and interpretation, introducing latency, downlink bandwidth constraints, and limited operational responsiveness. By embedding a VLM on board the satellite, visual reasoning can be …