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A dynamic movement primitives-based tool use skill learning and transfer framework for robot manipulation
No full textThis paper presents a framework for learning and transferring robot tool-use skills based on Dynamic Movement Primitives (DMPs) for robot fine manipulation. DMPs and their enhanced methods are employed to acquire a specific tool-use skill applicable to tools with similar sizes, shapes, and uses. However, the acquired skills may not be transferable to other scenarios and tools with variations. The new framework introduces two new types of skills based on DMPs: Object Operating (O2) skill and Tool Flipping (TF) skill. The O2 skill enables robots to handle tools for manipulating objects to achieve desired effects. The learning process for the O2 skill considers limitations imposed by tools and the environment during human demonstrations. Distinguishing between whether constraints can be modelled or not, we propose both a model-based and a constraint-based method to separate a constraint-irrelevant (CI) skill and the constrained conditions. The CI skill is generalized using a novel method called constrained -DMP lite, enabling adaptation to new tasks with special tools. The TF skill addresses situations where tools must generate an action to alter contacting positions on both objects and tools while avoiding conflicts during movement. Finally, the TF and O2 skills are generalized to be applied in creating a continuous action chain. We conduct several experiments to compare and analyze the advantages and disadvantages of the proposed methods with other approaches in terms of generalizability and calculation complexity. Note to Practitioners —Strengthening robot tool-use ability has been a hot research topic in recent years because these tools can extend the reachability and enhance the flexibility of robots. The previous research on DMPs has been utilized for learning tool-use skills. However, the learned skills few considered the tools’ special use regulations, therefore the skill of using a tool is hard to transfer to another tool-use case. This paper explores tool-use skill learning and transfer between different tools by developing a framework based on the DMPs for this problem. The framework consists of two kinds of skills: O2 skill and TF skill with different purposes as well as a series of newly developed algorithms, such as constrained -DMP lite, a model-based and a constraint-based CI skill learning methods. These methods can separate the constraints from human demonstrations of using tools to achieve a CI skill and generalize the CI skill according to the constraints generated from a new tool-use manipulation task. We verify the effectiveness of the proposed framework through some typical tool-use experiments, including pushing objects, cutting and obstacle avoidance in actuality. The development of this framework can be used in industrial and house working scenarios
Clinical and cost effectiveness of paramedics working in general practice: A mixed-methods realist evaluation
Get PDFBackground:General Practice (GP) services are under pressure due increased demand . Alongside substantial national recruitment challenges, there exists a shortage of GPs to meet current need. Resultingly, allied healthcare professionals (AHPs), including paramedics, are being utilised in general practice. Aim:To determine the models of paramedics in general practice settings (PGP); mechanisms that underpin effective PGP; impact of PGP on safety, costs, clinical and patient reported outcomes and experience. Design:A mixed methods realist evaluation comprised of a rapid realist review followed by an evaluation of PGP in general practice case study sites. PPI input was integral, ensuring validity from a patients and carer perspective. Setting:General practices in England.Participants:Thirty four general practices participated as case study sites; 25 were PGP. Data from qualitative realist interviews (n=69), quantitative questionnaires (n=489) and electronic records (n=22,509 consultations) were collected.Interventions:PGP models were classified according to a) level of integration of the paramedic to the general practice team b) complexity of patients seen by paramedics.Main Outcomes Measures:Qualitative interviews investigated initial programme theories with staff and patient participants. Patient participant questionnaires utilised validated measures: the Patient Reported Experiences and Outcomes of Safety in Primary Care (PREOS-PC) (safety); EQ-5D-5L (health related quality of life); Primary Care Outcomes Questionnaire (PCOQ); the Modular Resource Use Measure (ModRUM) (health and care resource utilisation). Electronic health records provided data on primary care use. Review Methods:A rapid realist review of the published and grey literature, supplemented with direct enquiry with system leaders and key stakeholders. Results:The rapid realist review highlighted significant variation in paramedics' roles in general practice. Qualitative interviews identified domains related to access, safety, workforce reconfiguration, infrastructure, patient experience, and outcomes. Lower PREOS-PC practice activation scores were found at PGP sites (perceived less engaged in promoting safety) in particular those with medium and low levels of PGP integration and complexity. There was a small statistically significant difference in the PCOQ “Confidence in Health Plan” by PGP complexity, such that confidence had deteriorated slightly more in the high complexity group compared to non-PGP. PGP sites had lower scores at initial visit and 30 days for the PCOQ “Confidence in Health Provision”. We found little evidence that PGP care led to substantial spillover effects via increased re-consultations, prescriptions, secondary care referrals or unplanned hospital admission costs. Limitations:The study faced challenges in recruitment. Self-selected participating sites may not be representative of all GPs in England, and categorising PGP models for analysis was more complex than anticipated. The comparison of costs and outcomes between PGP and non-PGP sites was based on an observational study design. Conclusions:PGP care improves access to general practice. Safety and acceptability require resources for induction, supervision, training, and education. PGP integration affects staff satisfaction and role longevity. PGP allows paramedics to develop and evolve.Future work:Larger studies utilising different study designs with longer follow up are needed to fully understand the impact of PGP on clinical outcomes and episode of care costs.Study Registration:ISRCTN56909665 https://doi.org/10.1186/ISRCTN56909665 Funding:This project was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme and will be published in XXX Journal; Vol. XX, No. XX. See the NIHR Journals Library website for further project information.
Sensemaking through crisis: Critical Care Pharmacist (CCP) leadership during COVID-19
Get PDFPurpose - The purpose of this study is to understand how Critical Care Pharmacist’s (CCP) coped during the COVID-19 crisis by investigating what sense-making and leadership processes were evident during the crisis. Design/Methodology/Approach - Data from ten semi-structured interviews of Lead CCP’s across different NHS organisations in the UK was analysed through a thematic process.Findings - The findings identified that strong pre-existing relationships and high levels of trust play a significant role in successfully navigating a crisis. Four sense-making processes seem important to building and maintaining these relationships and trust – 1) Identifying cues for change; 2) Authoring and labelling; 3) Interpretation and storytelling; and 4) Negotiation and deliberation.Originality/ Value - The research also highlights the need for organisations to acknowledge the leadership roles undertaken by CCP teams and to leverage this role by investment in leadership training, thereby increasing resilience and preparedness for future storms or crises on the horizon
Comparative analysis of deep neural networks for service life prediction in turbofan jet engines
Get PDFTraditional maintenance solutions, such as unplanned repairs, periodic inspections, and manual record-keeping, struggle to handle growing industrial downtime costs. In the age of Industry 4.0, accurately predicting remaining useful life for aero-engine components is crucial for reducing unexpected downtime and optimising maintenance schedules. Predictive maintenance, utilising Industry 4.0 technologies such as machine learning, has the potential to significantly reduce these losses by predicting equipment faults and service life. This study thoroughly assesses five deep learning architectures; artificial neural network, LSTM, bidirectional LSTM (BiLSTM), gated recurrent unit (GRU), and convolutional neural network (CNN) for estimating the service life of turbofan jet engines. This study utilises seven subsets of NASA's C-MAPSS dataset (simulating 128 engines under various operating scenarios and failure types) and preprocess sensor and operational data through alignment, missing-value handling, and data normalisation. The models are trained with the Adam optimiser using early stopping, tested, and validated with stratified splits (70%/15%/15%). Performance is assessed using root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R²), NASA's asymmetric scoring function, and a unique composite score (S). The results indicate that GRU outperforms other models and is the most effective DL architecture for aero-engine prognostics, with lower RMSE, MAE, and NS, as well as the best R² and optimal composite score. Recurrent architectures (GRU, BiLSTM, and LSTM) maintained 78% of the top two performance ranks, demonstrating their effectiveness in modelling temporal degradation and predicting the aero-engines service life
Optimizing preoperative venous thromboembolism risk assessment in elderly hip fracture patients: A refined caprini model integrating D-dimer and injury-to-admission time
No full textBackground: The Caprini risk assessment model (RAM) is widely used to evaluate venous thromboembolism (VTE) risk across diverse patient populations. However, the original risk stratifications may require modification for hip fracture patients to improve predictive accuracy. This study aimed to optimize VTE prediction by refining the Caprini model and integrating additional predictive factors. Methods: This retrospective cohort study included 1114 elderly hip fracture patients screened at Peking Union Medical College Hospital between May 2012 and February 2023. A modified VTE prediction model was developed by integrating D-dimer levels and injury-to-admission time into the Caprini RAM. The sensitivity, specificity, and the area under the curve (AUC) of the model were determined to assess its predictive performance. Results: The revised Caprini model effectively stratified patients into three VTE risk levels on the basis of their scores: 14.0% for ≤9, 24.0% for 10–11, and 39.4% for ≥12. Both the Caprini score and risk level demonstrated better predictive ability than D-dimer did (AUCs: 0.606 and 0.614 vs 0.552). Among patients admitted within one day after injury, the D-dimer levels were significantly higher in VTE patients compared with non-VTE patients from day 3 onwards (p = .012). Incorporating the injury-to-admission time with the Caprini score further improved the AUC from 0.614 to 0.649. Among models maintaining the sensitivity and negative predictive value above 90%, this combination model demonstrated the best performance. In contrast, for patients with delayed admission (>1 day), D-dimer levels were significantly higher in those with VTE than in those without VTE (p < .001). Combining the Caprini score with the D-dimer level provided a more accurate prediction (AUC: 0.681), significantly outperforming the Caprini score alone (AUC: 0.552). When the sensitivity exceeded 95%, the D-dimer threshold model across the three Caprini risk levels outperformed the Caprini risk levels combined with the D-dimer level (AUC: 0.592 vs 0.571) and demonstrated a significant advantage at 100% sensitivity. Conclusions: Reclassifying the Caprini score into three risk levels may improve preoperative VTE stratification in elderly hip fracture patients. Integrating the injury-to-admission time and D-dimer level into the Caprini model was associated with improved predictive performance. Standardizing the timing of D-dimer sampling may reduce timing-related variability in VTE assessment. External multicentre validation is warranted
Cryptos ESG ratings and price crash risks
Get PDFCryptocurrencies operate in decentralized, fast-evolving ecosystems where environmental, social, and governance (ESG) factors may shape market behaviour. This study examines how ESG relates to price crash risk for 149 cryptocurrencies, offering a sustainability perspective on crypto assets. We extract ESG information from white papers and industry reports, develop criteria aligned with each asset’s mechanism and function, and assign environmental, social, and governance ratings. Crash risk, our proxy for sustainability, is measured using the negative coefficient of skewness (NCSKEW) and the down-to-up volatility ratio (DUVOL). To ensure coverage and comparability, we begin with the top 500 by market capitalisation as of 30 October 2024 and retain assets with data available from 1 October 2020. We use ANOVA and decision-tree models to test how ESG characteristics explain variation in crash risk. Our findings confirm that ESG considerations can enhance crypto market resilience, as higher ESG ratings are associated with lower crypto price crash risks. Cryptos at the relatively low-risk group (by NCSKEW or DUVOL) average E = 1.3 (max 3), S = 3.4 (max 6), and G = 2.2 (max 3). These insights provide practical guidance for investors, developers, and policymakers aiming to reduce risks and promote sustainability in the crypto ecosystem
Beyond aches and pain: The hidden economic burden of musculoskeletal conditions in children and adolescents
Get PDFCommentary on: Espirito Santo, C. M. et al. Overview of the economic burden of musculoskeletal pain in children and adolescents: a systematic review with meta-analysis. Pain 165, 296-323 (2024). https://doi.org:10.1097/j.pain.000000000000303
Building and sustaining freelance careers in a small nation: The case of Cardiff’s film and television industries
Get PDFOften characterised as an occupational group of highly skilled, responsive, resilient and creative individuals, freelancers make a vital contribution to the strength and sustainability of film and television production. Freelancers are both intrinsically situated in the places they work through the interrelations of local authorities, cultural institutions and the labour market, and are themselves placemakers, contributing to the local milieu through building place-based communities to mitigate the inherently precarious nature of their careers. Based on in-depth interviews with freelancers and screen agencies in Cardiff, this paper explores the complex relationships between creative workers and their locality. It exams how freelancers negotiate precarious careers in a small nation through the support of local development agencies and government intervention. In doing so, this work builds on previous research concerning freelancer labour in Bristol, furthering the contention that place-based interventions and policy occupies an important role in nurturing diverse and resilient regional production sectors
Student responses to climate knowledge: Enabling climate concern to flourish
Get PDFPurpose: This paper aims to examine a co-produced initiative implemented at the [University Name] between September 2022 and April 2023. The student-led project (Climate, Conversations and Cake: The 3C’s) addressed environmental and climate crisis awareness through monthly gatherings where, in partnership, students, academic staff and professional personnel gathered to share food, engage in conversations and partake in joint activities. Design/methodology/approach: This paper draws upon a mix of student and staff feedback, gathered through surveys and written/verbal reflections, to explore the value and impact of this project. Findings: The project received two [University Name] student Union awards for teaching sustainability and for student welfare, and was a finalist in the UK and Ireland Green Gown Awards. The 3C’s provided a platform for emotional expression by fostering a safe and supportive environment and encouraged students to reflect, share, apply and deepen their learning experiences in an informal setting characterised by compassion and empathy. This paper highlights the importance of developing supportive and compassionate pedagogical practices which recognise and normalise climate concern. Originality/value: The findings contribute to the growing body of literature on co-produced projects within higher education institutions, showcasing the potential of such initiatives to encourage meaningful engagement and empower students in addressing the pressing challenges of climate crisis. In addition to providing an evidence base for the value of such initiatives, through outlining the specifics of this student-led project, a framework that can be used by other institutions to develop their own initiatives is offered