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Silver Saplings Adventures for Older People: a qualitative review and evaluation of intended positive interventional change and wellbeing effects for participants of the programme.
Get PDFThe Silver Saplings Adventures (SSA) programme is a nature-based wellbeing intervention targeting older people, located in Moray, Aberdeenshire and areas of the Highlands. It consists of monthly day trips to outdoor settings, providing opportunities for participants to engage within communities, connect with others, as well as learn about and from their local natural environment. The SSA programme has been purposively designed in this way to promote individual wellbeing, social cohesion and feelings of inclusivity. This report presents a focused, independent evaluation of the SSA programme, based on a sample of 17 participants who engaged with the 12-month programme during its third (and penultimate) cycle, spanning January – December 2023. Evaluating the SSA programme was undertaken to optimise the development and continuation of the programme beyond its current funding, and to inform the transferability of this to other similar programmes and contexts. The primary objective of this evaluation was to assess the SSA programme to ascertain any wellbeing effects on participants, how these effects manifested and the broader ramifications, and to identify what specific aspects of the programme might be responsible for generating these reported effects
A comparative study of novelty detection models for zero day intrusion detection in industrial Internet of Things.
No full textThe detection of zero-day attacks in the IoT network is a challenging task due to unknown security vulnerabilities. Also, the unavailability of the data makes it difficult to train a machine learning (ML) model about new vulnerabilities. The existing supervised ML-based Intrusion Detection Systems (IDS) are trained to detect only known attacks. On the contrary, the unsupervised ML-based IDSs show a high false-positive rate. In this paper, we experimented on three novelty detection algorithms named One-Class SVM (OCSVM), Local Outlier Factor (LOF), and Isolation Forest (IF), which follow the one-vs-all strategy for zero-day-intrusion detection for IoT datasets. UNSW-NB15 and IoTID20 datasets are considered for the experiment. Experimental results show that OCSVM outperformed the other two models for zero-day intrusion or unseen anomaly detection in IoT domain
"Doing" is never enough, if "being" is neglected: exploring midwives' perspectives on the influence of an emotional intelligence education programme: a qualitative study. [Article]
Get PDFThe role of the midwife is emotionally demanding, with many midwives experiencing high levels of stress and burnout, and a great number considering leaving the profession. This has serious implications for the delivery of high-quality, safe maternity care. One of the major factors leading to job dissatisfaction is the conflict between midwives' aspiration of truly 'being' with the woman and the institutional expectations of the role, which focuses on the 'doing' aspects of the job. 'Being' present to a woman's psychological needs, whilst meeting the institutional demands, requires high levels of emotional intelligence (EI) in the midwife. Therefore, enhancing midwives' EI could be beneficial. An EI programme was made available to midwives with the intention to promote their emotional intelligence and enable them to utilise relaxation techniques for those in their care. The aim of this study was to explore midwives' perspectives on the influence of the EI education programme on their emotional wellbeing and experiences of practice. The study took a descriptive qualitative approach. Thirteen midwives participated in focus group interviews. The data were analysed using thematic analysis. The overarching theme of 'The Ripple Effect' included three themes of 'Me and my relationships', 'A different approach to practice', and 'Confidence and empowerment'. The programme was seen to create a positive ripple effect, influencing midwives personally, their approach to practice, and feelings of confidence in their role. The study concluded that EI education can reduce emotional stress in midwives, enhance their empathy and feelings of confidence, and thereby improve the quality of care that they provide
Understanding the impact of antenatal care policies in Georgia (USA) and Scotland (UK): a textual synthesis. [Preprint]
Get PDFThis study aims to: 1) understand the role of policy in maternal health outcomes; and 2) establish any differences or similarities between health systems, providing benchmarks for future maternal and infant care policies in Georgia and Scotland. Guided by JBI methodology, a textual review of policies and public health interventions that have influenced the antenatal care process in both health systems was conducted. Inclusion criteria for this review were classified using the "PCC" mnemonic: Population (pregnant women and mothers), Concept (policies and strategies that support prenatal and maternal health) and Context (relevant to Scotland and Georgia). Published primary and secondary research, and grey literature (guidelines, reports, and legislation from authoritative sources) were included. Overall, 60 sources contributed to the report on maternal health system topics. Findings of the textual synthesis presented a regionalized system of maternity care led by physician-provided care models in Georgia compared to the nationalized health system in Scotland with an extended scope for midwife-led care models. On a secondary, organizational level, Scotland also widely operates on protocolized, standardized care informed by clinical guidelines such as NICE. The Georgia health systems also follow national guidelines for care, but extent of standardization may vary based on a mixed system of private and public insurance coverage. This is the first study to comprehensively examine maternal health policies in the distinct contexts of Georgia and Scotland, shedding light on the diverse approaches within their respective healthcare systems. These observed variations stem from historical, cultural, and policy contexts unique to each region. As the United States continue to prioritize maternal and child health through public health initiatives, our findings feature crucial considerations for maternal antenatal care policies. Specifically, there is a discernible need to increase access to antenatal care and invest in the maternity care provider workforce, revealing opportunities for targeted improvements in support of maternal health
Comparative effect size distributions in strength and conditioning and implications for future research: a meta-analysis.
Get PDFControlled experimental designs are frequently used in strength and conditioning (S&C) to determine which interventions are most effective. The purpose of this large meta-analysis was to quantify the distribution of comparative effect sizes in S&C to determine likely magnitudes and inform future research regarding sample sizes and inference methods. Baseline and follow-up data were extracted from a large database of studies comparing at least two active S&C interventions. Pairwise comparative standardised mean difference effect sizes were calculated and categorised according to the outcome domain measured. Hierarchical Bayesian meta-analyses and meta-regressions were used to model overall comparative effect size distributions and correlations, respectively. The direction of comparative effect sizes within a study were assigned arbitrarily (e.g. A vs. B, or B vs. A), with bootstrapping performed to ensure effect size distributions were symmetric and centred on zero. The middle 25, 50, and 75% of distributions were used to define small, medium, and large thresholds, respectively. A total of 3874 pairwise effect sizes were obtained from 417 studies comprising 958 active interventions. Threshold values were estimated as: small = 0.14 [95%CrI: 0.12 to 0.15]; medium: = 0.29 [95%CrI: 0.28 to 0.30]; and large = 0.51 [95%CrI: 0.50 to 0.53]. No differences were identified in the threshold values across different outcome domains. Correlations ranged widely (0.06 ≤ r ≤0.36), but were larger when outcomes within the same outcome domain were considered. The finding that comparative effect sizes in S&C are typically below 0.30 and can be moderately correlated has important implications for future research. Sample sizes should be substantively increased to appropriately power controlled trials with pre-post intervention data. Alpha adjustment approaches used to control for multiple testing should account for correlations between outcomes and not assume independence
Optimized common features selection and deep-autoencoder (OCFSDA) for lightweight intrusion detection in Internet of things.
Get PDFEmbedded systems, including the Internet of things (IoT), play a crucial role in the functioning of critical infrastructure. However, these devices face significant challenges such as memory footprint, technical challenges, privacy concerns, performance trade-offs and vulnerability to cyber-attacks. One approach to address these concerns is minimising computational overhead and adopting lightweight intrusion detection techniques. In this study, we propose a highly efficient model called optimized common features selection and deep-autoencoder (OCFSDA) for lightweight intrusion detection in IoT environments. The proposed OCFSDA model incorporates feature selection, data compression, pruning, and deparameterization. We deployed the model on a Raspberry Pi4 using the TFLite interpreter by leveraging optimisation and inferencing with semi-supervised learning. Using the MQTT-IoT-IDS2020 and CIC-IDS2017 datasets, our experimental results demonstrate a remarkable reduction in the computation cost in terms of time and memory use. Notably, the model achieved an overall average accuracies of 99% and 97%, along with comparable performance on other important metrics such as precision, recall, and F1-score. Moreover, the model accomplished the classification tasks within 0.30 and 0.12 s using only 2KB of memory
A novel multi-factor fuzzy membership function- adaptive extended Kalman filter algorithm for the state of charge and energy joint estimation of electric-vehicle lithium-ion batteries.
No full textIn view of the unmeasurable state parameters of electric-vehicle lithium-ion batteries, this paper investigates a novel multi-factor fuzzy membership function - adaptive extended Kalman filter (MFMF-AEKF) algorithm for the online joint estimation of the state of charge and energy. Strong nonlinear characteristics of model parameters are characterized by considering multiple processing factors of electrochemical and diffusion effects for lithium-ion batteries and constructing an optimized multifactor coupling model. In the proposed MFMF-AEKF method, multi-space-scale factors are introduced to realize the numerical analysis of the multi-factor coupled model parameters and state estimation under dynamic working conditions of electric-vehicle lithium-ion batteries. The proposed MFMF-AEKF algorithm estimates the state of charge (SOC) with the overall best mean absolute error (MAE), mean absolute percentage error (MAPE), root mean square error (RMSE), and maximum error (ME) values of 1.822%, 4.322%, 1.947%, and 2.954%, respectively, under challenging working conditions. And The MAE, MAPE, RMSE, and ME values for the state of energy (SOE) are 0.617%, 1.711%, 0.695%, and 1.011%, respectively. Both state estimation results are better than the traditional method. The proposed MFMF-AEKF algorithm has higher estimation accuracy which provides a feasible estimation algorithm for the joint SOC and SOE of lithium-ion batteries
Distal-extremity cryotherapy in preventing chemotherapy-induced peripheral neuropathy from paclitaxel administration in people affected by breast cancer: a systematic review.
Get PDFTo explore the experiences of utilising distal-extremity cryotherapy in reducing chemotherapy-induced peripheral neuropathy during Paclitaxel treatment on physical functioning, clinical and patient-reported outcomes, compared to standard care in people affected by breast cancer. Four databases and one register were searched on 11 April 2023 to identify all relevant studies meeting the inclusion and exclusion criteria. These were CINAHL (via EBSCOhost), Cochrane Central Register of Controlled Trials, Medline (via EBSCOhost), Scopus, and Web of Science Core Collection, with no limiters placed on any of the searches. Additionally, relevant systematic reviews were scrutinised for potentially relevant studies for screening. Distal-extremity cryotherapy is a safe intervention with minimal risk for serious adverse events. However, insufficient data supports the mainstay clinical use of cryotherapy in reducing chemotherapy-induced peripheral neuropathy from Paclitaxel use within the breast cancer population. Heterogeneity in study design, cryotherapy mode, and measurement tools underscore the need for additional research. Despite limited data on the impact of distal-extremity cryotherapy in preventing chemotherapy-induced peripheral neuropathy, there are valuable implications for nursing practice arising from this review. Nurses play a vital role in the clinical and experiential journey of people with breast cancer, it is important that they understand the available evidence and act as patient advocates. Assisting patients in understanding current research and encouraging participation in future studies, thereby enhancing our knowledge, and strengthening the available evidence base
Advancing AI with green practices and adaptable solutions for the future. [Article summary]
Get PDFDespite AI's achievements, how can its limitations be addressed to reduce computational costs, enhance transparency and pioneer eco-friendly practices
Eco-friendly thick and wear-resistant nanodiamond composite hard coatings deposited on WC–Co substrates.
No full textNanodiamond composite (NDC) films, synthesized using an environmentally friendly PVD coaxial arc plasma deposition technique on commercial cemented carbide (Co6 wt%) substrates without the need for substrate heating, chemical etching of Co, and chemical gases. These NDC coatings, crafted under specific discharge power conditions (5.2 J/pulse, 120 V, and 1 Hz), with or without a substrate biasing (−100V, 40kHz, and 35% duty cycle), exhibit a distinctive nanostructure characterized by nanodiamond grains embedded in an amorphous carbon (a-C) matrix. Highlighting remarkable mechanical characteristics attributed to highly energetic ejected carbon ion. The coatings boast high hardness (H = 65–82 GPa), Young's modulus (E = 688–780 GPa), plasticity index (H/E = 0.094–0.105), and brittle fracture resistance (H3/E2 = 0.58–0.9 GPa). Additionally, these NDC films manifest a substantial thickness of 7 μm due to low internal stress, along with superior adhesion, anti-wear resistance, and a low friction coefficient (0.1–0.09) through dry sliding against an Al2O3 counterpart. Raman analysis substantiates the nanocomposite structure of the film, underscoring the influential role of biasing in enhancing the characteristics of these environmentally friendly and wear-resistant NDC coatings. Nevertheless, the application of a negative bias led to increased internal stress levels (1.28 to 4.53 GPa), adversely impacting the adhesion between the film and substrate, resulting in a decrease from HF3 to HF6 as per Rockwell C indentation. NDC coatings hold significant potential for extending the lifespan of cutting tools and improving overall machining performance