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Psychological safety as a predictor of acute stress, well-being and burnout in health and social care workers : a predictive correlational study
Get PDFBackground: Health and social care workers (HSCWs) experience high levels of stress, burnout and emotional strain. Psychological safety is increasingly recognised as a protective factor, yet limited research has examined how individual psychological safety and team psychological safety jointly contribute to mental health outcomes in frontline care environments. Methods: A total of 821 HSCWs completed validated measures assessing individual psychological safety (NPSS), team psychological safety (TPSS), well-being, burnout and acute stress. Correlational analyses and hierarchical regression models were used to evaluate the unique and shared contributions of individual and team psychological safety to each outcome. Results: Both NPSS and TPSS were significantly associated with well-being, burnout and acute stress. Team psychological safety emerged as the strongest predictor of burnout and acute stress, accounting for substantial additional variance beyond individual psychological safety, with increases in explained variance ranging from 0.14 to 0.16. For well-being, NPSS (β = 0.38) and TPSS (β = 0.36) were both significant predictors. TPSS demonstrated large effects for burnout (β = 0.67) and acute stress (β = 0.72). Conclusions: Psychological safety plays a central role in the mental health of HSCWs. Team-based psychological safety was particularly influential in protecting against burnout and acute stress, while individual neuroceptive safety remained important for supporting overall well-being. Strengthening both individual and team-level psychological safety may enhance resilience and reduce psychological risk within health and social care settings. Implications: Incorporating NPSS and TPSS within workforce assessment may support early identification of psychological vulnerability, inform trauma-informed organisational interventions and promote more resilient, supportive workplace cultures
Hydrogen–diesel dual-fuel combustion in marine medium-speed engines : knocking suppression by direct water injection at high hydrogen substitution ratios
Get PDFHydrogen is among the most promising alternative fuels for achieving zero-carbon emissions in the maritime sector. However, its application in marine engines faces the bottleneck of substitution ratio limitation. The primary reason is the risk of knocking resulting from hydrogen's rapid heat release and high flame speed. The aim of this study is to explore in-cylinder direct water injection as a knocking-suppression strategy to enable higher hydrogen fractions in the engine. Two knocking-free operating modes are investigated: low hydrogen substitution ratios (0–40 %) without water injection and high hydrogen substitution ratios (90 and 95 %) with water injection. The results show that without water injection, the maximum hydrogen substitution ratio that can maintain stable combustion is 30 %, resulting in a 2.96 % improvement in indicated thermal efficiency and a 3.11 g/kWh rise in NOx emission. With direct water injection, knocking-free combustion can be achieved at high hydrogen substitution (90 and 95 %) under specific injection timing. At the suggested control point of 90 and 95 % HSR (1.5 water-to-fuel ratio, and −100 °CA water injection timing), a 1.43 % and 1.39 % improvement in indicated thermal efficiency and a 6.01 g/kWh and 6.45 g/kWh reduction in NOx emissions can be achieved compared to pure diesel mode. These findings indicate that in-cylinder direct water injection effectively increases hydrogen substitution ratios while enabling high thermal efficiency and low emissions, making it a promising approach for hydrogen–diesel dual-fuel marine engines
Transient Au-Cl adlayers modulate the surface chemistry of gold nanoparticles during redox reactions
Get PDFControlling surface chemistry at the nanoscale is essential for stabilizing structure and tuning function in plasmonic, catalytic and sensing systems, where even trace ligands or ions can reshape surface charge and reactivity. However, probing such dynamic interfaces under operando conditions remains challenging, limiting efforts to engineer nanomaterials with precision. Here, using in situ surface-enhanced Raman spectroscopy, we identify a transient Au-Cl adlayer that forms during electrochemical cycling at gold interfaces. The adlayer exhibits significant charge transfer between gold and chlorine, generating an outward-facing dipole that polarizes neighbouring atoms and modulates the local potential. This dipole stabilizes nanogap interfaces and directs oriented ligand rebinding, enabling reversible reconstruction of subnanometre architectures. It also alters interfacial charge distributions and mediates electron transfer between gold oxidation states, acting as a redox-active intermediate. These findings show how transient surface species shape nanoscale reactivity and stability, offering strategies for designing catalysts, sensors and nanomaterials. [Abstract copyright: © 2025. The Author(s).
Generative self-supervised learning for seismic event classification
No full textDeep learning has been widely applied to seismic signal classification, predominantly through supervised learning, typically relying on large labeled datasets. However, since the process of labeling large volumes of seismic data by domain experts is time-consuming and prone to human error, labeled seismic datasets are scarce. To address the problem of limited labeled data availability, a novel approach for seismic event classification is proposed employing self-supervised learning techniques. Initially, a generative-based self-supervised learning model, specifically an auto-encoder, is designed to extract informative features from the Short Time Fourier Transform of seismic recordings. These features are classified into four categories: earthquakes, micro-earthquakes, rockfalls, and anthropogenic noise. Classification is performed using (a) unsupervised K-means clustering on unlabeled data and (b) semi-supervised approaches, where only 5 to 33.3% of the data are labeled. The proposed semi-supervised method achieves high performance on a publicly available Résif dataset with recall of 0.90 for earthquakes, 0.65 for micro-earthquakes, 0.91 for rockfalls, and 0.84 for noise signals when trained with 20% of the labeled data. Additionally, we introduce a novel method to improve data labeling efficiency by using Self-Organizing Maps to cluster features from large datasets into multiple nodes. Our results demonstrate that the experts can more effectively and confidently label a small number of nodes instead of labeling all the events in the large dataset, thereby reducing the experts’ workload to just 4.6% of the original effort and our study reveals that this approach provides an excellent trade-off between expert labeling effort and classification accuracy, making it a highly effective solution for seismic event labeling. To evaluate the generalization capability of our proposed self-supervised learning model, we tested it on two unseen seismic datasets: the globally distributed Stanford Earthquake Dataset and the regionally focused Pacific Northwest Curated Seismic Dataset. On Stanford Earthquake Dataset, the pre-trained model effectively extracted discriminative earthquake and noise features, achieving high clustering accuracies. The Pacific Northwest Curated Seismic Dataset further challenges generalization with heterogeneous and previously unseen event types such as explosions, and thunder. Despite this diversity, the pre-trained model still preserved meaningful feature separability and captured inter-class relationships among acoustically similar events. Overall, these findings highlight the model’s ability to generalize effectively across both global and regional seismic datasets, underscoring its potential for wide deployment in seismological monitoring and event characterization without extensive retraining
Teleneuropsychology in Latin America : Experiences and challenges during the COVID-19 pandemic
No full textThe COVID-19 pandemic accelerated the use of teleneuropsychology (TeleNP) to deliver remote neuropsychological services in settings with limited clinic access. Objective: To examine TeleNP practices in Latin America (LA), focusing on clinicians’ perceptions of utility, validity, and barriers. Methods: A descriptive, exploratory cross-sectional survey was conducted between November 2020 and January 2021 among health professionals practicing neuropsychology in LA. The instrument, validated through a Delphi process, assessed professional background, TeleNP use, patient profiles, applied tests, and perceived advantages and challenges. Results: A total of 212 clinicians from 10 countries participated (mean age and clinical experience = 42.7 years and 12.3 years, respectively). Participants were primarily psychologists (75.9%), but also neurologists, geriatricians, psychiatrists and speech-language pathologists. TeleNP adoption rose from 4.2% regular and 13.7% occasional pre-pandemic use to 58% at the time of the survey, with significant cross-country variation (χ² = 79.0, df = 30, p < .001). TeleNP was used mainly for patient (90%) and informant (89.5%) interviews, screening (71.8%), and, in half of the cases, more extensive assessments. The advantages reported were improved access (81.5%), reduced transportation costs (79.8%), patient comfort (66.1%), and easier scheduling (66.1%). The main barrier identified was limited patient connectivity (84.7%). Regulatory knowledge was heterogeneous: 36.7% reported TeleNP authorization in their country, 23.5% reported no authorization, and 39.8% were unsure. Conclusion: TeleNP adoption in LA increased during the pandemic and is perceived as a valid, accessible modality to address geographic disparities in neuropsychological care. However, heterogeneous implementation, regulatory uncertainty, and technological limitations remain major challenges, underscoring the need for standardized guidelines
Does negative buzz result in social media discontinuation? : Investigating the effects of negative word of mouth in the United States, India, and Finland
Get PDFNegative Word-of-mouth (WOM) significantly influences how users form attitudes toward digital platforms, yet little is known about its role in social media discontinuation. Grounded in Social Cognitive Theory (SCT), this study investigates how two types of negative WOM, online and offline, influence users’ perceptions of privacy and social media discontinuation intent among WhatsApp users in the United States (n = 309), India (n = 271), and Finland (n = 205). The research model conceptualizes negative WOM as environmental factors, privacy invasion, and distrust as self-judgment, and discontinuation intention as the behavioral response. The structural equation modeling shows that users do not respond to both types of WOM in the same way in different countries. Online negative WOM significantly increases perception of privacy invasion in the US and India, while offline negative WOM is more influential in shaping distrust in Finland. Distrust consistently predicts discontinuation intention across three countries, with privacy invasion directly affecting discontinuation intention only in Finland. This study contributes to existing literature by examining the impact of environmental factors represented in both offline and online negative WOM, as well as cognitive factors represented in privacy invasion and distrust on discontinuous intention. Further, unlike the mainstream literature that focuses on a single country, we study social media discontinuation across three countries. The research advances SCT-based research by applying it to the underexplored domain of social media discontinuation and provides implications for designing country-specific privacy strategies to mitigate discontinuation risks
Meeting of minds : imagining the future of child and youth mental health research from an early career perspective
Get PDFChild and youth mental health is an international public health and research priority. We are an interdisciplinary and cross-sectoral network of UK-based early career researchers (ECRs) with an interest in child and youth mental health research. In this paper, we reflect on ongoing challenges and areas for growth, offering recommendations for key stakeholders in our field, including researchers, institutions and funders. We present a vision from an ECR perspective of what future child and youth mental health research could look like and we explore how the research infrastructure can support ECRs and the wider research field in making this vision a reality. We focus specifically on: (a) embracing complexity; (b) centring diverse voices; and (c) facilitating sustainable research environments and funding systems. We present recommendations for all key partners to consider alongside their local contexts and communities to actively and collaboratively drive progress and transformative change
An Early Shift to Low-Carbon Fuel Production at the Sullom Voe Terminal ('SVT') Could Provide the Backbone for a Successful Transition of the Shetland Economy
Get PDFUsing our Shetland Economy Model (‘SEM’) to conduct scenario simulations informed by a combination of local authority data and industry projections, this policy brief addresses the question of whether Veri Energy’s proposed Phase 1 of low-carbon fuel production at the islands’ Sullom Voe Terminal could mitigate total job losses across Shetland and local GDP leakage associated with the projected decline in oil processing activity at the terminal. We find that while the more capital-intensive terminal and local supply chain activity means that while job losses can be minimised, there may still be some capacity freed up in Shetland labour market, which could be positive given the need to roll-out multiple low carbon projects in the remote island context (where it can be challenging to bring in and accommodate more workers). However, a central finding and insight emerging is that the net impact on Shetland’s local GDP is positive in all timeframes. That is the positive impacts of Phase 1 of LCF production at SVT more than offset the negative impacts of the decline in oil processing activity on total income generation in each and every year of deployment and operation. Thus, we conclude that early action supporting LCF production at Shetland’s Sullom Voe Terminal is an essential step in laying the foundation for the UK’s net zero ambitions and avoiding negative transition outcomes like those recently experience in Scotland around Grangemouth and Mossmorran
Developments & potential of nanotechnology for the detection and treatment of pancreatic cancer
Get PDFPancreatic cancer is projected to become the second leading cause of cancer death by 2030 with a dismal 5-year survival rate compared to other cancers (12%). Due to the absence of clear early symptoms, diagnosis is often delayed resulting in many patients presenting with advanced disease and limited treatment options. Surgery remains the only potential curative option. However, only about 20% of cases are detected early enough for surgery. Consequently, most patients rely on chemotherapy, immunotherapy and radiotherapy. Among these, chemotherapy offers the best chance of tumor shrinkage, it comes with many problems such as harsh side effects which kill healthy cells and cancer cells, leaving the patient sometimes too ill to continue treatment. With immuno- and radiotherapy, it offers limited success in the treatment of pancreatic cancer despite its success in treating other forms of cancer. Nanotechnology offers promising opportunities for more effective diagnosis and less aggressive treatment. Fortunately, there has been some success for pancreatic cancer with two nano formulations currently approved by the Food and Drug Agency (Onivyde and Abraxane) offering greater survival rates and reduced side effects compared to traditional chemotherapy. Unfortunately, progress in nanotechnology-based diagnostics for pancreatic cancer remains limited. However, numerous different types of nanoparticles are under investigation in preclinical and clinical studies showing positive results. This review gives an overview of the potential of nanotechnology within this area looking at harnessing its potential in more effective diagnosis strategies and for more efficient therapy
Influence of WEC geometric variables on the performance of an integrated WEC–VLFS system
Get PDFThis study proposes a novel integrated concept that combines a wave energy converter (WEC) array with an interconnected very large floating structure (VLFS), aiming to provide a solution capable of harvesting wave energy while simultaneously protecting offshore structures. A numerical model of the integrated system is developed using the discrete–module–beam (DMB) method together with the Lagrange multiplier technique. After validating the accuracy of the simulation approaches, the influence of WEC geometric variables on the system performance is evaluated, including the energy capture performance of the WECs and the hydroelastic response of the VLFS. Five WEC geometric variables are examined: length, gap, number, draft and shape. Due to the complexity of the analytical model, deriving an optimal damping coefficient for the power take-off (PTO) device is challenging; therefore, it is determined through numerical search. A series of simulations show that, compared with the other four variables, the integrated system is most sensitive to the WEC length. Moreover, incorporating the WEC array effectively reduces the hydroelastic response of the VLFS, particularly under short-wave conditions. In addition, within a three-unit WEC array, the central WEC exhibits a significantly higher power capture efficiency than the side units. The methodology and findings of this study can provide useful insights for the preliminary design of similar integrated systems
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