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Practitioner Guidance for Implementing Low-Volume High Intensity Interval Training in People with Coronary Artery Disease
Get PDFObjectiveHigh intensity interval training (HIIT) is recognised within many international cardiac rehabilitation (CR) guidelines. In the United Kingdom (UK), however, similar guidance does not exist; moderate intensity training regimens have traditionally been advocated. The aim is to develop a pragmatic technical report for practitioners working in CR in order to implement low-volume HIIT programmes for people with coronary artery disease (CAD).MethodsWe describe patient inclusion and exclusion criteria, clinical and safety considerations, and practical implications to support the implementation of low volume HIIT in practice. Detailed methodology relating to low-volume HIIT using the 10 ×1minute model is provided, alongside exercise training progression criteria.ResultsWe provide corresponding percentage heart rate reserve (%HRR) training thresholds which can be used to guide individualised exercise prescription. Key considerations for familiarisation, supervision, monitoring, recording, and reporting are also discussed, underpinned by an overview of the acute physiological response to the training modality.ConclusionsWe anticipate that this pragmatic evidence-based technical report will support practitioners in implementing low-volume HIIT in routine clinical practice, thus, allowing it to be offered as standard-care alongside more traditional moderate intensity exercise training programmes
University-industry collaboration and enterprise total factor productivity
Get PDFThis study evaluates how university-industry collaboration (UIC) affects total factor productivity (TFP). Based on unbalanced panel data of Chinese listed manufacturing enterprise between 2002 and 2022, our analysis reveals that: (1) UIC significantly enhances TFP; (2) the impact pathways through which UIC affects TFP include human capital, R&D investment, and management efficiency; (3) the effect of UIC on TFP is heterogeneous across firms' innovation capabilities, ownership types, and regional location; (4) the effect of UIC on TFP exhibits regional spillover effects. These findings provide valuable insights into how to leverage UIC to drive enterprise innovation, transformation, and upgrading
Energy Consumption Framework and Analysis of Post-Quantum Key-Generation on Embedded Devices
Get PDFThe emergence of quantum computing and Shor's algorithm necessitates an imminent shift from current public key cryptography techniques to post-quantum-robust techniques. The NIST has responded by standardising Post-Quantum Cryptography (PQC) algorithms, with ML-KEM (FIPS-203) slated to replace ECDH (Elliptic Curve Diffie-Hellman) for key exchange. A key practical concern for PQC adoption is energy consumption. This paper introduces a new framework for measuring PQC energy consumption on a Raspberry Pi when performing key generation. The framework uses both the available traditional methods and the newly standardised ML-KEM algorithm via the commonly utilised OpenSSL library
Effects of environmental conditions on mate fidelity in a socially monogamous seabird
Get PDFIn iteroparous, socially monogamous species, individuals vary in the extent of mate fidelity across breeding attempts, often with important fitness consequences. Numerous studies have demonstrated intrinsic drivers of mate fidelity, notably previous breeding success and parental age. Environmental conditions may also influence mate fidelity, and the habitat-mediated hypothesis predicts that fidelity will be lower when environmental conditions are poor. However, limited testing of this hypothesis has been undertaken in longitudinal studies of single populations. Furthermore, studies have mainly focused on environmental conditions during the breeding season, yet conditions prior to breeding may be important for mate fidelity because this is a critical period for pair bond formation. We investigated the effects of prebreeding environmental conditions (onshore wind component and sea surface temperature) on mate fidelity over a 20-year period in the socially monogamous, iteroparous, long-lived marine bird, the European shag, Gulosus aristotelis. Average fidelity rate varied three- to four-fold between years. Mate fidelity was affected by prebreeding environmental conditions, being lower when onshore winds were more prevalent and sea surface temperature was higher. However, mate fidelity was more strongly affected by intrinsic factors, with higher rates when breeding success in the previous attempt and population density were higher, and among older females and middle-aged males. We found that mate fidelity affected timing of breeding, with faithful pairs laying earlier, and early laying pairs bred more successfully, but there was no independent effect of mate fidelity on breeding success. Our results support the habitat-mediated hypothesis whereby prebreeding environmental conditions affect individual pairing decisions. Given environmental conditions are predicted to change globally, further investigation of their impact on aspects of social behaviour in a range of species is warranted
Nitrate Pollution Mapping for Reservoirs Using Flexible Sensors Integrated with Underwater Robot
Get PDFWater pollution monitoring is crucial for environmental protection, playing a key role in safeguarding ecosystems, protecting public health and promoting sustainable development. However, traditional methods face challenges related to accessibility, real-time analysis and spatial coverage. In this study, we developed a sensor-integrated advanced deployment system for mapping water pollutant parameters. For this, a new voltametric nitrate monitoring sensor is developed using a screen-printing method. Here, for the sensor, the active electrode is composed of a Cu₂O-graphene composite paste, a printed Ag|AgCl reference electrode, and a carbon-based printed counter electrode, all integrated onto a single polyester flexible substrate. The developed sensor exhibits a sensitivity of 3.41 µA/µM within the range of 0 to 0.5 µM of NaNO3. The repeatability, selectivity analysis and performance of various bending angles (0-40 degrees) reveal its implementation in water pollution monitoring. The performances also reveal the possibility of large-scale manufacturing of printed sensors in environmental pollution monitoring. To improve sensor deployment strategies and optimize data acquisition for real-time water quality monitoring, the sensor was incorporated into a remotely operated vehicle (ROV) and tested at different depths and locations in a water container. The ROV, with its advanced navigation and adaptability, can offer an efficient solution for detecting chemical pollutants, mapping hydrothermal plumes, and autonomously adjusting missions based on in situ measurements. The developed system demonstrates the potential of low-energy electrochemical sensors for environmental monitoring applications. This study contributes to advancing ROV-based sensor networks for tracking pollution sources and optimizing water quality assessment in dynamic aquatic environments
Positive Symptoms of Psychosis and International Classification of Diseases 11th Revision (ICD-11) Complex Post-traumatic Stress Disorder: A Network Analysis in a Canadian Sample from Montreal
Get PDFObjectives: Traumatic experiences constitute a risk factor for developing different psychopathologies, such as post-traumatic stress disorder (PTSD), complex post-traumatic stress disorder (CPTSD), and positive symptoms of psychosis. However, on the symptom level, it is still unclear how CPTSD and positive symptoms of psy-chosis associate with each other. The present study aimed to shed light on these dy-namics by investigating the symptoms network of CPTSD and positive symptoms of psychosis. Methods: A network analysis was performed on CPTSD and psychosis symptoms among a Canadian community sample with a history of traumatic life events (n = 747). Measures included the International Trauma Questionnaire (ITQ) and the mPRIME screen. Results: 4.8% of the sample reached the criteria of probable PTSD; 7% fulfilled the criteria of probable CPTSD. PTSD and CPTSD groups had a significantly higher severity of positive symptoms of psychosis compared to the no-disorder group. Net-work analysis revealed three distinct communities of symptoms of PTSD, disturbances in self-organization, and psychosis. Affective dysregulation served as the bridging symptom between the communities. Hearing one’s own thoughts aloud was the most central symptom in the network. Conclusions: Findings show that positive symptoms of psychosis can be considered trauma-related responses. Further, interventions targeting affective dysregulation as well as the experience and distress associated with hearing one’s own thoughts aloud may contribute to symptom reduction and improved functioning
A Digital Twin model for predicting wind turbine performance using federated learning
No full textGenerating electricity from wind power is a crucial aspect of any renewable energy strategy, and onshore and offshore wind farms are among the most effective renewable energy sources. However, existing wind turbines and farm management have significant drawbacks, as wind turbines are distributed, and data collection, monitoring, configuration, and optimization need to be improved. Additionally, onsite data processing is necessary for network efficiency, privacy, and security. This study proposes a Digital Twin (DT) modeling architecture to emulate wind turbine operations and data workflows through virtual containers at the edge. The proposed system employs the Federated Learning (FL) algorithm with Age of Twin (AoT) data sampling based on Root Mean Square Error (RMSE) differences. This approach ensures reactive data sampling to maintain the freshness of the DT model data. This approach constructs global wind turbine models by processing and training at the edge, eliminating the need for centralized data aggregation. The wind energy model forecasts power generation with Deep Sequential Neural Networks (Deep Seq. NN) and XGBoost Machine Learning (ML) algorithms to evaluate model performance with two different datasets for homogeneous and heterogeneous wind turbine environments. The results show that the proposed models have a 0.9952 prediction accuracy with a 0.0354 Root Mean Square Error (RMSE) in the homogeneous environment, and 0.9949 value and 0.0396 in the heterogeneous environment. In addition, it has been demonstrated that the FL method can utilize AoT to achieve highly identical DTs with a reactive algorithm
Perspectives on the roller-coaster of becoming a teacher: Surfacing pre-service teacher voice through poetry.
Get PDFThis study sought to examine the lived experiences of pre-service teachers in Scotland as they undertake a one-year post-graduate teaching qualification (PGDE). Part of the work in this intensive qualification year is to reconcile shifting understandings of what it means to become and be a teacher. The aim was to surface authentic descriptions of the experience of student teachers as they reflect on and develop their expectations, identities and values in relation to being a teacher. Data collection was in the form of original poems created by the students at the end of their year of study. This approach was chosen to allow for emotionally honest responses, making use of the immediacy and inherent economy of language that poetry offers. Thematic analysis was applied to the data. Areas for teacher educator reflection are identified. These include recognising the challenges that come with navigating shifting understandings of both the practice and the purpose of the job as well as the consequent emotional work the qualification year entails
High-Performance Multiport Antenna with Frequency Selective Surface for 5G Ka-Band Applications
No full textThis paper presents a novel multiport antenna tailored for 5G millimeter-wave (mm-Wave) applications. The proposed design features orthogonally arranged radiating elements to ensure compactness with an overall footprint of just 20 × 26 mm². A key innovation is the integration of a Frequency Selective Surface (FSS) layer placed above the antenna system to enhance gain and isolation without increasing complexity. This FSS enhances gain by 1.5 dB across the band, achieving a peak gain of 7.5 dBi at 41 GHz. The antenna operates across the entire Ka-band (22-46 GHz), delivering efficiency exceeding 80% and maintaining isolation above 20 dB. Key multiport antenna performance parameters including diversity gain (DG = 10) and envelope correlation coefficient (ECC < 0.005) align with performance benchmarks, and experimental measurements validate simulation results. The unique combination of orthogonal element placement and FSS enhancement positions this antenna as a robust solution for next-generation 5G applications. Keywords: Multiport antenna, 5G mm-Wave, Ka-band, Frequency Selective Surface (FSS), compact antenna. Key Points: 1) A MIMO antenna integrated with a FSS is designed for 5G mm-Wave applications operating across an ultra-wide bandwidth of 22-46 GHz. 2) A key innovation lies in the integration of a FSS layer above the MIMO structure that significantly enhances the radiation characteristics. 3) The proposed FSS-based MIMO antenna offers a compact, high-efficiency, and wideband solution for next-generation 5G mm-Wave devices
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