University of Limerick Research Repository

This paper proposes a compliant ortho-planar spring piezoelectric vibrational energy harvester (COPS-PVEH) using a H-I structure that exploits a nonlinearity and an asymmetric mono-stability to enhance the bandwidth of the device. The main structure is based on a double clamped beam (I-structure) coupled with four cantilever beams (H-structure) and an ortho-planar spring in the centre of the I-structure. Finite element analysis (FEA), analytical modelling, and experimentation were performed to analyse the dynamical and electrical behaviour of the harvester. The device was fabricated using polylactide (PLA). Six bimorph PZT-5H piezoelectric materials, electrically connected in parallel, were used as piezoelectric generators. The device was tested using an optimum load resistor of 90 kΩ under sinusoidal and sine sweep excitation in the gravity (vertical) direction. The pre-load (due to gravitation) causes a softening nonlinearity and an asymmetric mono-stability in the potential energy function. The results show that multiple peaks are observed in the output voltage of the harvester in the FEA, analytical modelling, and experimentation under harmonic excitation in the sub 15 Hz frequency range. Furthermore, analytical modelling and experimentation exhibit softening nonlinearity and chaotic behaviour, reaching a maximum amplitude power of 1.01 mW (at 8.3 Hz) and 1.07 mW (at 9.5 Hz) respectively under sine sweep excitation (amplitude of 0.6 g (g = 9.81 m/s2 )). Experimentally, the harvester also generates an average power greater than 46 µW with a 6.8 Hz bandwidth under the same excitation. The softening nonlinearity and asymmetric mono-stability enhance the bandwidth of the harvester in the low frequency region where most broadband ambient vibrations are available in practical environments.

This chapter sets out the policy context for people with intellectual disabilities interfacing with police as accused persons in Ireland. Against a backdrop of relevant international obligations, it outlines recent research-based developments in this field. It further sets out to discuss domestic safeguards that shape the treatment of individuals at this interface. It discusses five key safeguards in this context: access to a solicitor, right to medical assistance, access to specialist interviewers, the responsible adult safeguard, and accessible information. Recommendations are made to offer policymakers a blueprint for legislative and procedural reform that promises to align Irish criminal procedure with the human rights exigencies mandated under international conventions.

The development of sustainable and tunable materials is crucial for advancing modern technologies. We present a controlled synthesis of colloidal Na–Cu–S nanostructures. To overcome the reactivity difference between Na and Cu precursors toward chalcogens in a colloidal synthesis and to achieve metastable phase formation, we designed a single-source precursor for Cu and S. The decomposition of this precursor creates a Cu–S template into which Na ions diffuse to form metastable Na–Cu–S. By leveraging the reactivity of sulfur precursors, we synthesized Na3Cu4S4 (orthorhombic) and Na2Cu4S3 (monoclinic) nanocrystals with distinct properties. A mechanistic investigation reveals a predictive pathway previously unobserved in alkali-metal-based ternary chalcogenide systems. Further, computational DFT calculations demonstrate that Na3Cu4S4 exhibits metallic characteristics while Na2Cu4S3 is semiconducting, with an optimal band gap for photovoltaic applications. This research advances our understanding of ternary chalcogenide systems and establishes a framework for the rational design of complex nanomaterials.

Purpose – There is growing recognition that effective project control systems (PCS) are critical to the success of projects. The relationship between the individual elements of PCS and successfully achieving project objectives has yet to be explored. This research investigates the enablers and barriers that influence the elements of PCS success and drive project objectives. Design/methodology/approach – This study adopts a mixed approach of descriptive analysis and regression models to explore the impact of six PCS elements on project outcomes. Petroleum and chemical projects in Saudi Arabia were selected as a case study to validate the research model. Findings –Data from a survey of 400 project managers in Saudi’s petroleum and chemical industry reveal that successful PCS are the key to achieving all project outcomes, but they are particularly critical for meeting project cost objectives. Project Governance was identified as the most important of the six PCS elements for meeting project objectives. A lack of standard processes emerged as the most significant barrier to achieving effective project governance, while having skilled and experienced project team members was the most significant enabler for implementing earned value. Practical implications – The study offers a direction for implementing and developing PCS as a strategic tool and focuses on the PCS elements that can improve project outcomes. Originality/value – This research contributes to project management knowledge and differs from previous attempts in two ways. Firstly, it investigates the elements of PCS that are critical to achieving project scope, schedule and cost objectives; secondly, enablers and barriers of PCS success are examined to see how they influence each element independently.

This work demonstrates the use of Deep Learning-based Computer Vision for Remanufacturing end-of-life consumer electronics products, considering smartphones as the use-case. We implemented automated detection of screen defects such as scratches and cracks. In turn, this could lead to increased reuse of smartphones in a secondary market alongside new ones to meet consumer demand. The refurbishment of smartphone devices is a growing industry heavily dependent on manual labor, making decisions subjective, especially in grading the severity of damage. A critical analysis of defect detection and smartphone grading from a remanufacturing perspective is conducted. This analysis is significant in a remanufacturing sector that deals with dynamically varying input of cores (used products for remanufacturing), characteristics, timing, and number of returns. The solution we propose here is novel in its own right, requiring data analysis and collection, data curing, defect parameterization, and dataset building to enable model-based training and detection experiments. We collected and annotated a dataset to detect and grade the various defects based on their severity. A range of deep learning models was trained on the dataset to obtain baseline results for the state-of-the-art deep learning detection models, including YOLOv7, YOLOv8, YOLO11 variants, and Mask R-CNN. Our experiments also showed improved precision values when the pre-trained models were pre-fine-tuned using a road crack segmentation dataset before training on our phone defect dataset. The inference time for the YOLOv8x model is 8ms. This reduced inference time with a high precision of 70.4% indicates that a consistent, fast, and accurate grading is achieved here, ensuring a high throughput rate in the remanufacturing process and ensuring sustainability

Adults who have substantial histories of homelessness and complex support needs may feel ambivalent about integrating into their communities and find it difficult to do so. Being familiar to and recognized by others as a resident in a neighborhood or community are sources of “distal support” that provide individuals with feelings of belonging to their community and are important to recovery from homelessness. We hypothesized that individuals engaged with Housing First (HF) programs would report more distal support than individuals engaged with traditional homeless services (treatment as usual, TAU), and that distal support would predict more community integration, growth‐related recovery, and achieved capabilities. We analyzed data collected from homeless services users (n = 445) engaged with either HF or TAU in eight European countries. Measures included achieved capabilities, growth‐focused recovery, distal supports, and community integration. Serial mediation analyses confirmed our hypothesis that the effects of HF on growth‐related recovery and achieved capabilities are indirect, mediated by distal supports and community integration. Findings are discussed in relation to the importance of modeling the effects of HF on social and psychological outcomes as indirect and identifying important mediators that translate the effects of HF components on social and psychological outcomes. We also note the importance of case management activities that encourage clients to develop and sustain distal supports with others who live and work in their neighborhoods.

This chapter considers nineteenth-century Irish Gothic literary production, beginning with the Romantic-era ‘trade Gothic’ and culminating in the ghost stories of the fin de siècle. Acknowledging the significance of the texts that have now become synonymous with ‘the Irish Gothic’, the argument nevertheless probes the primary position they have been accorded in Irish literary historiography, questioning the process of literary canonisation that has marginalised large swathes of Irish Gothic writing. It thus offers an analysis of lesser-known texts that highlight the diverse range and scope of Irish engagement with the Gothic mode, from the ‘first wave’ Gothics (1790s to early 1800s) that were often condemned as mere imitations of Ann Radcliffe, to mid-century periodical publications that demonstrate the continued influence of the Gothic mode in Ireland even after the demise of ‘the Gothic novel’. It furthermore queries the understanding of Irish Gothic as a predominantly Protestant literary mode written almost exclusively by men, exploring the rich body of Catholic Gothic texts as well as the central contribution made by women writers to the mode’s development.

The ‘agency’ question is long‐standing in psychological contract (PC) research: Who is the target party when a PC is created? Rousseau (1995), reflecting on the various organisational agents involved in working relationships, suggested that ‘most contract makers are individuals acting as the organisation's agents, who communicate demands and expectations upon which employment, advancement, remuneration, and retention are predicated’ (p. 60). Although administrative contract makers such as policies and HR practices are also historically recognised (Rousseau and Greller 1994; Suazo et al. 2009), the primacy of the ‘human’ contract maker in PC research has been central (Guest and Conway 2002).Yet, the rapid emergence of algorithmic‐enabled forms of employment in the gig economy disrupts the idea that the PC target party is always a human agent (Duggan et al. 2020). Digital labour platforms (DLPs) act as technological intermediaries to connect customers with service‐providing, independent freelancers in an on‐demand manner to carry out-short‐term tasks. It is in this context that we raise the fundamental question of whether a worker can create a PC with a non‐human agent in the form of an algorithm that mediates their relationship with an organisation. The implications of this question compel a fresh look at the features of PC Theory and its assumption

The prototype approach provides a theoretically supported basis for novel research, detailing “typical” cognitive representations of targets in question (e.g., groups, experiences). Fairly recently, in social and cognitive psychology, this approach has emerged to understand how people categorize and conceptualize everyday phenomena. Although this approach has previously been used to study everyday concepts, it has predominantly been overlooked in cross-cultural research. Prototype analyses are flexible enough to allow for the identification of both universal and culture-specific elements, offering a more comprehensive and nuanced understanding of the concept in question. We highlight theoretical, empirical, and practical reasons why prototype analyses offer an important tool in cross-cultural and interdisciplinary research while also addressing the potential for reducing construct bias in research that spans multiple cultural contexts. The advantages and risks of conducting prototype analyses are discussed in detail along with novel ways of integrating computational approaches with traditional prototype-analyses methods to assist in their implementation.