Middlesex University

Objectives To examine the association between muscle strength and cardiorespiratory fitness (CRF) with all-cause and cancer-specific mortality in patients diagnosed with cancer, and whether these associations are affected by type and/or stage of cancer. Method A systematic review with meta-analysis was carried out. Five bibliographic databases were searched to August 2023. Results Forty-two studies were included (n=46 694). Overall, cancer patients with high muscle strength or CRF levels (when dichotomised as high vs low) had a significant reduction in risk of all-cause mortality by 31–46% compared with those with low physical fitness levels. Similarly, a significant 11% reduction was found for change per unit increments in muscle strength. In addition, muscle strength and CRF were associated with an 8–46% reduced risk of all-cause mortality in patients with advanced cancer stages, and a 19–41% reduced risk of all-cause mortality was observed in lung and digestive cancers. Lastly, unit increments in CRF were associated with a significant 18% reduced risk of cancer-specific mortality. Conclusion High muscle strength and CRF were significantly associated with a lower risk of all-cause mortality. In addition, increases in CRF were associated with a reduced risk of cancer-specific mortality. These fitness components were especially predictive in patients with advanced cancer stages as well as in lung and digestive cancers. This highlights the importance of assessing fitness measures for predicting mortality in cancer patients. Given these findings, tailored exercise prescriptions to improve muscle strength and CRF in patients with cancer may contribute to reducing cancer-related mortality.

Circular Manufacturing (CM) is a manufacturing process that employs strategies such as remanufacturing and closed-loop supply chains to improve sustainability (Delpla, Kenné, & Hof, 2022). This process employs circular economic principles. The adoption of CM has been impeded by a lack of financial support, inadequate consumer awareness, and insufficient government support. This review aims to facilitate a broader understanding of the adoption of government policies in implementing circular manufacturing strategies, which will help in advancing our knowledge about how nations compete to create and capture value. To provide a comprehensive and global perspective, the review included 524 studies from the Scopus Database, covering studies between 1990 and May 2024. The review contributes to (a) outlining three thematic clusters of shared scholarly interest, (b) the conceptual framework, and (c) highlighting several areas for future research. Ineffective management and sharing of information are significant challenges that impede organisational knowledge and decision-making administration. The transition to CM is facilitated by identifying essential data and technologies through an integrative review (bibliometric analysis and conceptual framework).

Introduction: There is currently little research relating specifically to the muscular strength and endurance requirements of the upper body such as lifts at varying heights, ground floor contact with the hands and inversions such as handstands. Enhanced understanding of muscular demands can inform training program design to build physical tolerance to meet the demand of the activity. The aim of this study was to ascertain the frequency of upper body muscular skills in contemporary and ballet dance performance. Methods: Analysis of 46 individual ballet performers (F = 23, M = 23) from 12 performances (duration 63.5 ± 44.5 minutes) and 44 individual contemporary performers (F = 21, M = 23) from 12 performances (duration 35.7 ± 4.3 minutes) was carried out. Frequency of upper body skills was recorded using Dartfish Easytag-Note and converted to mean frequency per minute of total performance and per performance by genre and by sex. Differences in frequency between genre were analyzed via Mann–Whitney U. Phase two analyzed differences between sex via Mann–Whitney U. Finally, analysis of differences between sex within dance genre was carried out via Wilcoxon signed rank test. Significance was accepted at P < .05. Results: A significant difference was apparent between ballet and contemporary dance for holding own weight ( P < .05) with a greater total mean frequency within contemporary performances of 8.50 ± 9.03 compared to a total mean frequency of 1.51 ± 3.13 within ballet performances. Additionally, there was a significant difference for above shoulder assisted lift ( P < .05) when comparing male dancers, with male contemporary dancers carrying out significantly more (9.82 ± 8.56) per performance than male ballet dancers (2.33 ± 4.66). A higher mean frequency of below shoulder lifts than above shoulder lifts was also noted, with the majority of above shoulder lifts remaining at eye level. Conclusion: Training programs must prepare dancers for upper body movements that consider differing biomechanical demands of a variety of lifts and inversions.

This study aimed to verify the correlations between variables obtained from dry-land tests and swimming performance, in addition to examining the associations between the dry-land asymmetries and swimming performance. Thirty-seven male swimmers performed a test battery, including shoulder isokinetic torque, shoulder range of motion (ROM), vertical jump, anthropometric, and in-water force tests. Additionally, the best official performance in the events of 50 and 200 m front crawl were obtained. Interlimb asymmetries were calculated for all tested metrics, and Pearson and Spearman’s correlations were used to determine the association between the metrics (and their asymmetries) and swimming performance. Results showed that most of the dry-land metrics were significantly associated with 50 m front crawl (r = -0.59 to -0.83) and 200 m front crawl (r = -0.48 to -0.62) performance, and with peak force at tethered swimming (r = 0.54 to 0.80), except the ROM test (r = -0.22 to 0.33). None of the asymmetries originating from the dry-land tests were significantly correlated with swimming performance (ρ = -0.29 to 0.34). In conclusion, most dry-land outcomes measured are related to swimming performance, while the dry-land inter-limb asymmetries are not.

Police data is an important source of information for researchers about investigations, suspects, and victims. However, crime records can be problematic to work with. Here we outline three key issues along with our approach. We discuss data quality, which reflects missing and misclassified values; inconsistency, which refers to the vague and at times different definitions provided; and granularity, which reflects the lack of detailed information included in the datasets. We recommend developing a robust strategy for working with missing data, triangulating across different sources, creating higher-order categories where necessary, and creating a detailed data governance plan before analysis begins.

Hazard vulnerability assessment of critical infrastructures (CIs) is crucial for ranking infrastructures based on their level of criticality, enabling the urban managers to prioritize CIs for allocating funds in the hazard mitigation/recovery process. This study aims to provide a framework for ranking CIs based on a rapid and preliminary flood vulnerability assessment by introducing a methodology for classifying CIs according to their vulnerability to riverine flooding. An indicator‐based vulnerability curve is calculated both quantitatively (using Fuzzy Logic Toolbox in MATLAB) and qualitatively (using susceptibility–exposure matrix), based on which CIs prioritization is accomplished with a focus on functional flood vulnerability considering structural/nonstructural damages. Besides, this study addresses the consequences that a damaged infrastructure may have on the rest of CIs and estimates their vulnerability given the additive impact of the surrounding failed infrastructures considering their interdependence. The methodology was applied to Berat (Albania) and Sarajevo (Bosnia‐Herzegovina) with findings compared to those of a multi‐criteria decision‐making‐based approach commonly used in CI ranking literature. The obtained results from both methods represent that roads are the most vulnerable studied infrastructure in the case of Berat, while regarding the city of Sarajevo, road infrastructures are considered the least vulnerable to riverine floods compared to bridges and schools.

Purpose Domestic violence and abuse (DVA) cases remain under-reported and under-prosecuted in the criminal justice system (CJS), with researchers frequently having limited access to raw police data. Here, a range of factors relating to DVA offences occurring between 2018 and 2020 in one large English police force were described and measured. As part of the research, it was investigated if victim, suspect and crime characteristics predicted outcome decisions, specifically charge rate, case attrition, and evidential difficulties despite victims’ support in pursuing the allegations. The number of offences meeting the DVA legal definition, and those falling outside that definition, were also explored. Methods Univariate and multivariate logistic regressions were performed to predict the relationship between demographic information and criminal history on three coded crime outcome categories (namely, ‘charge’, ‘victim does not proceed’, and ‘law does not pursue’). Results The dataset included 198,617 crimes, and for 94.1% of them, the suspect was not charged. Relationship type, age, crime type, and the number of victim allegations predicted all three outcomes. For instance, being partners of the victim significantly decreased the chances of a charge compared to suspects who were not partners. Conclusions The findings are in line with evidence from the literature which highlights all-time low charge rates for DVA and high levels of victim attrition. We argue that the influence of victim/suspect characteristics and DVA-related dynamics should be considered by police personnel and members of the CJS when assessing crime reports.

Visual attribution in medical imaging seeks to make evident the diagnostically-relevant components of a medical image, in contrast to the more common detection of diseased tissue deployed in standard machine vision pipelines (which are less straightforwardly interpretable/explainable to clinicians). We here present a novel generative visual attribution technique, one that leverages latent diffusion models in combination with domain-specific large language models, in order to generate normal counterparts of abnormal images. The discrepancy between the two hence gives rise to a mapping indicating the diagnostically-relevant image components. To achieve this, we deploy image priors in conjunction with appropriate conditioning mechanisms in order to control the image generative process, including natural language text prompts acquired from medical science and applied radiology. We perform experiments and quantitatively evaluate our results on the COVID-19 Radiography Database containing labelled chest X-rays with differing pathologies via the Frechet Inception Distance (FID), Structural Similarity (SSIM) and Multi Scale Structural Similarity Metric (MS-SSIM) metrics obtained between real and generated images. The resulting system also exhibits a range of latent capabilities including zero-shot localized disease induction, which are evaluated with real examples from the cheXpert dataset.

Hybrid recommender systems use advanced algorithms to learn from heterogeneous data sources and give consumers customized recommendations. User preferences (like ratings or reviews) and item content (like description or category) are two examples of the data that might be included. In earlier research on recommender systems, user feedback, or "ratings," was primarily used to construct user profiles and assess recommendation quality. Even if ratings are helpful, they might not give a complete picture of users' preferences. On the other hand, some feedback data—such as reviews and the emotions they convey—represent people and their preferences in a different or complementary way. Such information might highlight significant aspects of a user's profile that aren't always associated with user ratings; as a result, it may show a different aspect of the user. In this study, we provide a novel hybrid recommender system that analyzes heterogeneous data sources, such as user ratings and feelings gleaned from reviews, using sophisticated algorithms. Our method uses sentiment analysis to capture a more nuanced perspective of user preferences, in contrast to standard systems that build user profiles solely based on ratings. We employed sophisticated algorithms to provide recommendations for users who can incorporate extra data, such as the sentiment of the review. Our investigations revealed that in some cases (such as the music industry), the opinions expressed in user reviews do not always strongly correspond with the ratings. This suggests that emotion may represent a distinct facet of user preferences and serve as a substitute for other user feedback.

The study estimates the determinants of R&D expenditure in the UK by using sectoral data of eight large scale industries over time. We examined both traditional and exceptional however empirically plausible determinants of R&D using two alternative dynamic models. Pooled OLS, the Fixed Effects and the Random Effects models are used for estimation. We find that the size of R&D expenditure in the UK is smaller than many other industrial countries.. The largest amount of R&D expenditure in the UK, takes place for ‘machineries’ industry followed by ‘communication equipment’ and ‘post and telecommunication’ industries. Estimated results demonstrate that the market size, ratio of skilled to unskilled workers, and macroeconomic policies significantly affect R&D investment in the UK. Working hours of low, medium and high skilled workers’ significantly affect the R&D expenditure with different size effects. We also find that R&D expenditure is an industry specific phenomenon.

This paper adapts intra-firm influence strategies to an inter-firm context. In the process it retests the relationshipbetween coercive influence strategies and supplier performance. Qualitative data is drawn from interviews withmanagers in the Australian Recruitment Industry. Contrary to predictions, the findings show that suppliers usecoalitions and upward appeals to improve their performance in inter-firm relationships. This suggests that priorinfluence studies are not completely correct in their prediction of a negative relationship between coerciveinfluence strategies and performance in inter-firm relationships. And, it suggests that there may be two types ofcoercive influence strategies in inter-firm relationships. There are coercive influence strategies that hindersupplier performance and there are coercive influence strategies that aid supplier performance.

This paper investigates the extent to which the microfinance sector should be influenced by risk management policies from the banking industry. The increasing commercialisation of microfinance is resulting in a greater impetus to implement formal risk policies and practices. Such actions, if conceived with due care and attention to the purpose of microfinance, could be an important step for the industry. However, there is a danger that generic procedures of risk assessment and management, particularly those adapted from purely for-profit industries, could impede this relatively young industry, or subvert its mission. The discussion centres around a survey of public opinion on the riskiness of a range of investment options and the factors that influence investment decisions, seeking to determine whether the public’s perception of the riskiness might be affected by qualitative factors, such as societal benefits. The survey finds no relationship between overall risk perception and the qualitative factors tested, but does suggest that investment decisions can be explained by two opposing dimensions: social and financial. This leads to a number of implications for the evolution of risk management within the microfinance industry, and highlights dangers of focusing purely on technical risk.

Background: Lipedema is a chronic condition characterized by abnormal deposition of subcutaneous adipose tissue, leading to pain. The lack of internationally recognized diagnostic criteria complicates the characterization of pain. Physiological parameters such as pain pressure threshold (PPT) represent promising prognostic markers for diagnosing lipedema, yet they remain understudied. This study aimed to evaluate the reliability and validity of two pain pressure measurements, PPT and the hand-held sphygmomanometer (HHS) in lipedema. Methods: A total of 28 adult females diagnosed with lipedema were recruited. Both PPT, using a digital algometer, and HHS, using a manual aneroid HHS, were performed to assess pain in the lower limbs. The testing was performed in a standing position with PPT and HHS placed on the calf. Intraclass correlation coefficient (ICC) and coefficient of variation (CV) were employed to assess the within session reliability, while the validity between PPT and HHS was analyzed using R2 in a linear regression model. Results: The results showed excellent reliability for both PPT and HHS, with ICC indicating high consistency (ICC = 0.93 to 0.97) and CV showing acceptable scores (CV = 3.62% to 9.06%). In addition, good validity between PPT and HHS was also observed (R2 = 0.69 to 0.74), suggesting that HHS can be a reliable alternative to PPT for pain assessment in lipedema. Conclusion: These findings have important clinical implications, as they expand the knowledge of pain characterization in people with lipedema, potentially aiding in diagnostic refinement. In addition, a cost-effective and accessible method for assessing pain was examined (i.e., HHS), showing promising findings and providing an objective method to help diagnose lipedema.