Munster Technological University

Whey waste streams from dairy processing can present major challenges for the industry in terms of their further utilization and the environmental impact of disposal. However, these waste streams generally contain high concentrations of nutrients with the potential to act as substrates in bioprocesses to generate sustainable high-value products. In this work, we evaluated the use of salty whey (SW) and acid casein whey (ACW) as feedstocks for the microbial production of poly-3-hydroxybutyric acid (PHB), a renewable and biodegradable bioplastic. Five PHB-producing strains - Priestia megaterium DSM32, Cupriavidus necator DSM545, Azohydromonas lata DSM1123, Paraburkholderia fungorum DSM1749, and Halomonas halophila DSM4770 - were examined for growth and PHB production in ACW and SW. Compared with the control minimal salts medium, both whey types supported higher biomass yield with SW generally producing more biomass than ACW. In small-scale (50 mL) batch fermentations in salty whey, H. halophila DSM4770 produced the highest yield of PHB (1.06 g/L), while C. necator DSM545 achieved the highest yield in ACW (0.34 g/L). These 2 substrate-strain combinations were selected for scale-up to 500 mL batch fermentations. At this scale, PHB yields reached 0.30 g/L for C. necator DSM545 in ACW but only 0.34 g/L for H. halophila DSM4770 in SW. While PHB production from SW has been reported previously, this study is the first to demonstrate PHB production using ACW. These findings highlight the potential of SW and ACW as viable feedstocks for the microbial production of PHB, contributing to the valorization of dairy waste streams.

Abstract In Ireland, dairy farm enterprise gross margins have shown strong variation from year to year. This research evaluates the volatility of dairy farm gross margins using methods from both the income volatility and income inequality literature. Methods from the income inequality literature are used to decompose gross margins into the average difference between-farms over time (average performance) and the variability within-farms over time (volatility around the average). Dairy enterprise gross margins are expressed on a per litre basis. The methods are, therefore, accounting for changes in milk production during a period of large expansion in the aftermath of milk quota removal. A panel dataset from the Teagasc National Farm Survey in Ireland is used covering the period from 2015 to 2022. We apply the Arc Percentage change method to explore the extent of volatility in the returns to milk production. The Arc Percentage changes are large and reflect both improvements and dis-improvements in the gross margin per litre from year to year. The novelty of this research is that we decompose the variation in the returns to milk production into performance and volatility components. The decomposition results indicate that most of the variability in gross margins per litre are due to variations within-farm over time rather than differences between-farms in average performance. Thus, this research highlights the role of volatility in the returns to milk production and points to the need of better counter-cyclical tools to manage risk.

Artificial Intelligence (AI) is increasingly integrated into cybersecurity systems to enhance threat detection, incident response, and overall security posture. However, the deployment of AI technologies introduces significant ethical considerations t

Major life transitions, such as entering the workforce or retirement, often disrupt social ties and increase the risk of involuntary loneliness and social isolation. Smartphone use as a coping strategy during these periods is complex, but particularly relevant for young and older adults, who are especially vulnerable. While smartphones can facilitate social connection, they also carry a substantial risk of problematic use, which has been linked to reduced offline interaction, anxiety, and depression. Clear age-related patterns emerge: young adults more often rely on impulsivity-driven coping (e.g., disordered eating or substance misuse), whereas in older adults, digital engagement more frequently intersects with health-related vulnerabilities, including sleep disturbances, cognitive decline, and gut-brain interactions. Developing a comprehensive biopsychosocial model that integrates biological (e.g., gut microbiota diversity and metabolic markers), psychological (e.g., stress and emotion regulation), and social (e.g., relationships and daily routines) levels of analysis would help distinguish protective from risky digital use. Such an approach could also enable earlier identification of at-risk individuals and support the development of tailored, age-sensitive prevention and intervention strategies during major life transitions.

We present an integrated optomechanical force sensor that employs waveguide Bragg gratings (WBGs) embedded in microcantilevers, offering a compact, fully passive optical readout suitable for atomic force microscopy (AFM) applications. Using a fully coupled three-dimensional (3D) finite element framework, we simultaneously model cantilever deformation, stress-induced refractive index changes, and optical mode evolution, offering improved accuracy and efficiency over decoupled approaches. Our analysis shows that the Bragg resonance shift arises primarily from the photoelastic effect and the resulting inhomogeneous refractive index distribution, with negligible contribution from cantilever bending-induced grating period changes, clarifying a mechanism often oversimplified in previous studies. By examining both the magnitude and direction of the resonance shift at a fixed interrogation wavelength or across the full reflection spectrum, we demonstrate that both compressive and tensile forces can be detected, enabling directional, all-optical force sensing. Simulations indicate that nanoscale forces applied at the cantilever tip produce detectable Bragg wavelength shifts, achieving a maximum force resolution of approximately 0.62 nm/µN and a minimum detectable force of 1.6 nN (for a 1 pm wavelength resolution). Beyond AFM, these findings establish clear design rules for the development of highly sensitive, fabrication-tolerant, and fully integrated photonic force transducers with potential applications in biosensing, lab-on-chip applications, and scalable MEMS/NEMS sensor arrays. • Developed a fully coupled 3D FEM framework for WBG-integrated AFM sensors. • Simultaneously modeled mechanical stress, photoelasticity, and optical modes. • Identified that photoelastic effects, not geometric deformation, dominate response. • Revealed directional asymmetry between upward and downward cantilever bending. • Demonstrated that WBG placement and loading direction control sensitivity and linearity.

The proliferation in edge computing in consumer electronics has intensified the demand for efficient, privacy-preserving fine-tuning of large language models (LLMs) amid resource heterogeneity, and data regulations. Traditional federated and split learning methods are limited by central coordination, static partitioning, and high overhead. This paper introduces SplitGossip, a novel peer-to-peer (P2P) framework for fine-tuning distilled LLMs on consumer edge devices. It combines reinforcement learning (RL)-based adaptive model splitting, layer-wise Low-Rank Adaptation (LoRA), and compressed gossip synchronization with error-feedback and local differential privacy (DP). SplitGossip employs an RL agent to dynamically partition layers through a multiobjective reward, balancing energy, latency, and accuracy. Local training uses LoRA with gradients compressed through adaptive top-k sparsification and INT8 quantization. Experiments conducted on AWS-simulated edge clusters show that the proposed SplitGossip outperforms baseline methods across all metrics, i.e., F1-score, communication overhead, energy efficiency, and convergence rate.

Integrating large-scale antenna arrays is essential for overcoming capacity limitations in wireless communications. In this work, we examine a novel sixth-generation (6G) secure simultaneous wireless information and power transfer (SWIPT) system, wher

Social Impact Statement Plant biostimulants are substances that are obtained from a variety of sources and are applied in minute quantities to enhance plant growth and vigor. In this review, we detail how the use of plant biostimulants may contribute to efforts to achieving a number of the UN Sustainable Development Goals. We describe how the incorporation of plant biostimulants could have both environmental and societal benefits, from increasing food security, potentially improving soil health, and enhancing economic cooperation. However, to fully exploit the potential of plant biostimulants, consistency in performance as well as a broader awareness is essential to their adoption and integration into common agricultural practices. Summary Plant biostimulants (PBs) have been shown to increase crop yield, quality, improve nutrient uptake and tolerance to abiotic stress. They have previously been proposed as innovative solutions for sustainable agriculture, with the global market currently exceeding $3 billion and projected to triple within the next decade due to climate change challenges and growing awareness of their potential. The Sustainable Development Agenda, adopted by world leaders in 2015, set out 17 Sustainable Development Goals (SDGs) with 169 targets and 330 indicators to be achieved by 2030, providing a blueprint for a fairer and more sustainable society. Interest in PBs has expanded significantly in recent years, and they are increasingly described as environmentally friendly tools that can be integrated into conventional agricultural practices to improve crop performance. Their use can directly support societal‐based SDGs: Zero Hunger (SDG 2) and Responsible Consumption and Production (SDG 12), and environmental SDGs: Climate Action (SDG 13), Life Below Water (SDG 14), and Life on Land (SDG 15). They may also indirectly contribute to Decent Work and Economic Growth (SDG 8) and Partnerships for the Goals (SDG 17). PBs promote a more sustainable approach to agriculture by mitigating abiotic stress, increasing nutrient use efficiency, and enhancing soil health. This article highlights how PBs can contribute to achieving some of the SDGs and international climate targets such as the Paris Climate Agreement while also underscoring the need for more systematic and coordinated research to strengthen the evidence base, optimize their effectiveness, and support wider adoption.