Institute of Technology Sligo

Future flood dynamics in a lowland karst catchment draining into Galway Bay, Ireland, have been assessed under climate-change scenarios. Bayesian neural network model (BNN) was calibrated on 1980-2015 observations of rainfall, tides, and turlough flood volumes, yielding correlations of R = 0.95 (training) and R = 0.78 (overall). Projections driven by CORDEX under RCP 4.5 and 8.5 for 2016-2100 reveal ensemble-mean rainfall increases of 1.2mm decade-1 and 2.5mm decade-1, respectively, corresponding to flood-volume growth rates of 5 × 10⁶ m3 decade-1 and 1.1 × 107 m3 decade-1. Wavelet coherence indicated high-frequency coupling (> 0.7) between rainfall and floods under RCP 8.5 versus < 0.5 under RCP 4.5. Extreme-event analysis showed a 40% rise in joint 95th -percentile rainfall and flood-volume events under RCP 8.5 (p < 0.05). Generalized extreme-value fits to annual maxima for 2018-2037 versus 2080-2099 project that a historical 100-year storm becomes 1-in-16-year event under RCP 8.5. 10-year rolling 90th -percentile analysis revealed rapid intensification of upper-tail floods under RCP 8.5 than RCP 4.5. These findings demonstrated that high-emission pathways substantially amplify flood magnitudes and frequencies and underscores the utility of integrated statistical and machine-learning frameworks for robust flood-risk assessment and climate-adaptation planning.

Fold defects represent a prevalent and detrimental issue in the multi-directional die forging of complex valve bodies, often resulting in product rejection and increased manufacturing costs. In this study, a three-dimensional thermo-mechanical coupled finite element (FE) model was developed using Forge® software to simulate the multi-directional die forging process. The “marking grid” and “sensors” functionalities were employed to visualize and track the formation and evolution of fold defects throughout the entire forming process, thereby elucidating the underlying fold formation mechanism. The effects of three key process parameters—initial billet temperature, main punch speed, and friction coefficient between the billet and die—on fold depth and damage value were systematically analyzed. Orthogonal experiments combined with analysis of variance (ANOVA) were conducted to identify the optimal parameter combination. Results indicated that the friction coefficient had the most significant influence on fold formation and damage accumulation, followed by billet temperature, while punch speed had the least impact. The optimal parameters were determined to be a friction coefficient of 0.1, an initial billet temperature of 1200 °C, and a main punch speed of 30 mm/s. Production trials and fluorescent magnetic particle inspection confirmed the absence of fold and crack defects, and the final forged product closely matched the simulation predictions, validating the effectiveness of the optimized process.

Sand dams are water infrastructure, built across ephemeral sandy rivers, that increase water supply by creating an artificial sandy aquifer upstream of the dam. Despite their effectiveness and recent traction in the research and development arena, empirical data on their distribution and characteristics are scattered and largely unreported. This gap represents a major barrier for understanding the large-scale potential of such a Nature-based Solution and for planning new installations. This paper presents a global dataset of sand dam locations and dimensions, developed collaboratively by research and development experts. We collected sand dam information from several sources, including local sand dam organizations. The data was reviewed and integrated through visual inspection in Google Earth. Although most georeferenced sand dams are from Eastern and Southern Africa, this dataset is a first global inventory and represents an invitation for others working in sand dams around the world to contribute their data. The dataset supports research on the effectiveness of sand dams and can aid practitioners with science-based criteria for sand dam development.

Abstract Background The Advanced Nurse Practitioner (ANP) Frailty Clinic Audit Project was developed in response to the increasing recognition of frailty as a critical healthcare issue in our ageing population. The project aimed to evaluate the effectiveness of the newly established outreach ANP-Led Frailty Clinic in delivering timely and comprehensive care to older adults, improving patient outcomes and optimising healthcare resource utilisation. Frailty is a multidimensional syndrome that increases an individual's vulnerability to adverse health outcomes such as falls, hospitalisation, functional decline and mortality. There was a growing demand for specialised services to identify and manage frailty early, preventing unnecessary hospital admissions and promoting independence among older adults with direct referrals form General Practitioners. The audit sought to determine whether early interventions in the clinic led to improved patient outcomes reduced hospital admission and enhance quality of life. Understanding the clinics performance ensured future service development based in real-world data. Methods Prospective clinical audit was conducted (September 2023-December 2024 inclusive) Inclusion Criteria: Patients &amp;gt;65 years referred to the ANP Frailty Clinic by Geriatrician or General Practitioner Results A total of 95 patients were included in the audit. Ten primary referral issues were identified with cognitive impairment and polypharmacy emerging as the most frequent concerns. Following initial assessment at the clinic, 30 patients (31.5%) re presented to the Emergency Department. The reasons for readmission varied and included falls resulting in fracture, respiratory illness and in some cases death. These outcomes highlight the high vulnerability of the older population and underscore the importance of early intervention strategies. Conclusion The results suggest that while the clinic plays a critical role in early assessment and intervention, there is a need to further strengthen follow up care enhance integration with community services and implement proactive management plans to help reduce avoidable hospital admissions and improve long term patient outcomes.

The rapid expansion of Internet of Things (IoT) deployments across smart environments introduces critical security challenges, particularly at the device identity and physical layers. Traditional cryptographic methods and Distributed Ledger Technologies (DLTs), while valuable, often fail to account for the constrained resources of IoT devices and their susceptibility to physical-layer attacks. This paper proposes a scalable, lightweight security framework that integrates Physical Unclonable Functions (PUFs), Zero-Knowledge Proofs (ZKPs), and a permissioned blockchain to establish end-to-end trust in distributed IoT ecosystems. PUFs act as hardware-rooted trust anchors, enabling secure key generation and unclonable device identity without relying on non-volatile memory. ZKPs facilitate mutual authentication by allowing devices to prove legitimacy without revealing any identifying information. A permissioned blockchain acts as a decentralised verification and audit layer, immutably recording authentication events and ensuring tamper resistance with controlled governance. The proposed architecture is designed to counteract physical tampering, spoofing, and identity forgery while remaining computationally viable for resource-constrained IoT devices. This work presents the foundation for a robust, privacy-preserving, and decentralised security model, bridging the gap between hardware-level assurance and scalable trust in future IoT deployments.