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What Are the Differences in the Area of Profitability and Efficiency When Early and Late Adopters Are Analyzed Regarding the Basel III Leverage Ratio?
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Data available on the databases mentioned in the text.This research investigates whether banks that adopted new regulatory requirements earlier, such as Basel III, are more profitable, as well as more efficient, than banks that adopted these requirements later. In addition, all 138 banks are based in the G7 member countries, which are the most developed countries in the world. Also, banks are categorized into early and late adopters based on Basel III Leverage Ratio performance by using Fitch Connect. Moreover, profitability ratios, such as the Return on Equity, Return on Assets and efficiency ratio Operating Efficiency, were collected from Fitch Connect to analyze if early adopters were more profitable and efficient than the late adopters. Also, STATA is used to analyze descriptive statistics and a univariate analysis of both groups. Furthermore, the finding is that early adopters of the Basel III Leverage Ratio are not the more profitable or efficient firms compared to late adopters as anticipated. In addition, the results of early and late adopters do not differ that much in the analysis regarding profitability and efficiency ratios. This implies that it is not necessarily correct to assume that stricter regulation, such as Basel III, will negatively affect the profitability or efficiency of banks. In addition, these results are useful to regulators and policymakers of the G7 member countries for two reasons. Also, regulators can clearly see how banks are adopting new stricter regulation.This research received no external funding
Highly Superior Autobiographical Memory (HSAM): A Systematic Review
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Not applicable.Supplementary Information is available online at: https://link.springer.com/article/10.1007/s11065-024-09632-8#Sec23 .Individuals possessing a Highly Superior Autobiographical Memory (HSAM) demonstrate an exceptional ability to recall their own past, excelling most when dates from their lifetime are used as retrieval cues. Fully understanding how neurocognitive mechanisms support exceptional memory could lead to benefits in areas of healthcare in which memory plays a central role and in legal fields reliant on witnesses’ memories. Predominantly due to the rareness of the phenomenon, existing HSAM literature is highly heterogenous in its methodologies used. Therefore, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we performed the first systematic review on this topic, to collate the existing behavioural, neuroanatomical, and functional HSAM data. Results from the 20 experimental selected studies revealed that HSAM is categorised by rapidly retrieved, detailed and accurate autobiographical memories, and appears to avoid the normal aging process. Functional neuroimaging studies showed HSAM retrieval seems characterised by an intense overactivation of the usual autobiographical memory network, including posterior visual areas (e.g., the precuneus). Structural neuroanatomical differences do not appear to characterise HSAM, but altered hippocampal resting-state connectivity was commonly observed. We discuss theories of HSAM in relation to autobiographical encoding, consolidation, and retrieval, and suggest future directions for this research.Open access funding provided by Università degli Studi di Roma La Sapienza within the CRUI-CARE Agreement
Validated respiratory drug deposition predictions from 2D and 3D medical images with statistical shape models and convolutional neural networks
Get PDFData Availability: The data and code underlying the results presented in the study are available from https://doi.org/10.5281/zenodo.10512507 which provides a static link to our git repository (https://github.com/jvwilliams23/respiratory2Dto3Dpaper).Supporting information is available online at: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0297437#sec017 .For the one billion sufferers of respiratory disease, managing their disease with inhalers crucially influences their quality of life. Generic treatment plans could be improved with the aid of computational models that account for patient-specific features such as breathing pattern, lung pathology and morphology. Therefore, we aim to develop and validate an automated computational framework for patient-specific deposition modelling. To that end, an image processing approach is proposed that could produce 3D patient respiratory geometries from 2D chest X-rays and 3D CT images. We evaluated the airway and lung morphology produced by our image processing framework, and assessed deposition compared to in vivo data. The 2D-to-3D image processing reproduces airway diameter to 9% median error compared to ground truth segmentations, but is sensitive to outliers of up to 33% due to lung outline noise. Predicted regional deposition gave 5% median error compared to in vivo measurements. The proposed framework is capable of providing patient-specific deposition measurements for varying treatments, to determine which treatment would best satisfy the needs imposed by each patient (such as disease and lung/airway morphology). Integration of patient-specific modelling into clinical practice as an additional decision-making tool could optimise treatment plans and lower the burden of respiratory diseases.Funding: Simulations reported in this study were performed on Oracle cloud computing platform, funded by Open Clouds Research Environments (OCRE) ‘Cloud Funding for Research’. JW was funded by a 2019 PhD Scholarship from the Carnegie-Trust for the Universities of Scotland. The in vivo deposition data used in this study was obtained from a project sponsored by Air Liquide
Health conditions in spousal caregivers of people with dementia and their relationships with stress, caregiving experiences, and social networks: longitudinal findings from the IDEAL programme
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IDEAL data were deposited with the UK Data Archive in April 2020. Details of how the data can be accessed can be found here: https://reshare.ukdataservice.ac.uk/854293/.Acknowledgements:
We would like to acknowledge the support of the following research networks: NIHR Dementias and Neurodegeneration Specialty (DeNDRoN) in England, the Scottish Dementia Clinical Research Network (SDCRN) and Health and Care Research Wales. We gratefully acknowledge the local principal investigators and researchers involved in participant recruitment and assessment within these networks. We are grateful to the IDEAL study participants for their participation in the study and to members of the ALWAYs group and the Project Advisory Group for their support throughout the study. For the purpose of open access, the authors have applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising.Electronic supplementary material is available online at: https://static-content.springer.com/esm/art%3A10.1186%2Fs12877-024-04707-w/MediaObjects/12877_2024_4707_MOESM1_ESM.docx .Objectives:
Longitudinal evidence documenting health conditions in spousal caregivers of people with dementia and whether these influence caregivers’ outcomes is scarce. This study explores type and number of health conditions over two years in caregivers of people with dementia and subgroups based on age, sex, education, hours of care, informant-rated functional ability, neuropsychiatric symptoms, cognition of the person with dementia, and length of diagnosis in the person with dementia. It also explores whether over time the number of health conditions is associated with caregivers’ stress, positive experiences of caregiving, and social networks.
Methods:
Longitudinal data from the IDEAL (Improving the experience of Dementia and Enhancing Active Life) cohort were used. Participants comprised spousal caregivers (n = 977) of people with dementia. Self-reported health conditions using the Charlson Comorbidity Index, stress, positive experiences of caregiving, and social network were assessed over two years. Mixed effect models were used.
Results:
On average participants had 1.5 health conditions at baseline; increasing to 2.1 conditions over two years. More health conditions were reported by caregivers who were older, had no formal education, provided 10 + hours of care per day, and/or cared for a person with more neuropsychiatric symptoms at baseline. More baseline health conditions were associated with greater stress at baseline but not with stress over time. Over two years, when caregivers’ health conditions increased, their stress increased whereas their social network diminished.
Discussion:
Findings highlight that most caregivers have their own health problems which require management to avoid increased stress and shrinking of social networks.‘Improving the experience of Dementia and Enhancing Active Life: living well with dementia. The IDEAL study’ was funded jointly by the Economic and Social Research Council (ESRC) and the National Institute for Health and Care Research (NIHR) through grant ES/L001853/2. Investigators: L. Clare, I.R. Jones, C. Victor, J.V. Hindle, R.W. Jones, M. Knapp, M. Kopelman, R. Litherland, A. Martyr, F.E. Matthews, R.G. Morris, S.M. Nelis, J.A. Pickett, C. Quinn, J. Rusted, J. Thom. ESRC is part of UK Research and Innovation (UKRI). ‘Improving the experience of Dementia and Enhancing Active Life: a longitudinal perspective on living well with dementia. The IDEAL-2 study’ is funded by Alzheimer’s Society, grant number 348, AS-PR2-16-001. Investigators: L. Clare, I.R. Jones, C. Victor, C. Ballard, A. Hillman, J.V. Hindle, J. Hughes, R.W. Jones, M. Knapp, R. Litherland, A. Martyr, F.E. Matthews, R.G. Morris, S.M. Nelis, C. Quinn, J. Rusted. S. Sabatini was supported by an ESRC Postdoctoral fellowship (ES/X007766/1). This report is independent research supported by the National Institute for Health and Care Research Applied Research Collaboration South-West Peninsula. The views expressed in this publication are those of the authors and not necessarily those of the ESRC, UKRI, NIHR, the Department of Health and Social Care, the National Health Service, or Alzheimer’s Society. The support of ESRC, NIHR and Alzheimer’s Society is gratefully acknowledged. L. Clare and L. Allan acknowledge support from the NIHR Applied Research Collaboration South-West Peninsula. L. Allan additionally acknowledges support from the NIHR Exeter Biomedical Research Centre (BRC)
Tri-arm MIMO array antenna pair for mobile phone applications
Get PDFData availability: The raw data can be obtained on request from the corresponding author.An 8 × 8 tri-arm multiple-input multiple-output (MIMO) array using novel even–odd mode decouplers is presented. To decouple the directly connected driven ports on the tri-arm antenna pair, a T-shaped stub working as an even-mode decoupler and a narrow strip working as an odd-mode decoupler are elaborately introduced. Therefore, the even-mode and odd-mode impedances cross with the antenna input impedance, and a deep coupling zero is achieved at this cross frequency. Finally, the proposed 8 × 8 MIMO array was developed, fabricated, and measured for further performance verification. The measured results show that the proposed array can have a wide isolation bandwidth of 17.2 % with a compact size of 0.44λ0 × 0.08λ0 and zero clearance requirement on the ground plane. The diversity performances are also investigated with the measured worst envelope correlation coefficient less than 0.05.None declared
Support-Sample-Assisted Domain Generalization via Attacks and Defenses: Concepts, Algorithms, and Applications to Pipeline Fault Diagnosis
Get PDFThis article is concerned with domain generalization (DG), a practical yet challenging scenario in transfer learning where the target data are not available in advance. The key insight of DG is focused on learning a robust model that can generalize to the unseen domain by leveraging knowledge from the source domain. To this end, we propose a novel algorithm known as support-sample-assisted Adversarial Attacks (SSAA) for DG. In the SSAA algorithm, an attack–defense strategy is deployed to enhance the target model's generalizability and transferability. This strategy includes a nontargeted attack stage, during which attack samples are generated to form pseudotarget domains with near-realistic covariate shifts. Subsequently, in the model defense stage, a biclassifier structure is used to distinguish support samples from the generated attack samples. These support samples form a new decision boundary encompassing all unseen samples, prompting an extension of the existing decision boundary to meet these samples. Experimental results on cross-domain fault diagnosis tasks suggest that SSAA outperforms current state-of-the-art DG methods, indicating a promising avenue for further DG development.10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 61933007, U21A2019 and 62222312);
Hainan Province Science and Technology Special Fund of China (Grant Number: ZDYF2022SHFZ105);
10.13039/501100012226-Fundamental Research Funds for the Central Universities
R&D Program of Zhejiang Province of China (Grant Number: 2023C01022);
National Key Research and Development Program of China (Grant Number: YS2022YFB4500205);
Shanghai Science and Technology Innovation Action Plan Project (Grant Number: 22511100700);
Alexander von Humboldt Foundation of Germany
Improved Adversarial Transfer Network for Bearing Fault Diagnosis under Variable Working Conditions
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Data are contained within the article.Bearings are one of the critical components of rotating machinery, and their failure can cause catastrophic consequences. In this regard, previous studies have proposed a variety of intelligent diagnosis methods. Most existing bearing fault diagnosis methods implicitly assume that the training and test sets are from the same distribution. However, in real scenarios, bearings have been working in complex and changeable working environments for a long time. The data during their working processes and the data used for model training cannot meet this condition. This paper proposes an improved adversarial transfer network for fault diagnosis under variable working conditions. Specifically, this paper combines an adversarial transfer network with a short-time Fourier transform to obtain satisfactory results with the lighter network. Then, this paper employs a channel attention module to enhance feature fusion. Moreover, this paper designs a novel domain discrepancy hybrid metric loss to improve model transfer learning performance. Finally, this paper verifies the method’s effectiveness on three datasets, including dual-rotor, a Case Western Reserve University dataset and the Ottawa dataset. The proposed method achieves average accuracy, surpassing other methods, and shows better domain alignment capabilities.This work was supported in part by the Natural Science Foundation of China (No. 52175116), Major Research Programs of the Natural Science Foundation of China (No. 92060302), the Research Foundation of the Higher Educational Key Laboratory for Flexible Manufacturing Equipment Integration of Fujian Province, the Xiamen Institute of Technology, the National Key Science and Technology Infrastructure Opening Project Fund for Research and Evaluation facilities for Service Safety of Major Engineering Materials and the Aeronautical Science Foundation (No. 2019ZB070001). Also, this work was supported in part by the Royal Society award (number IEC\NSFC\223294) to Asoke K. Nandi. Jun Wang acknowledges the financial support from the Innovative Leading Talents Scholarship and Brunel University London
Prop-oriented world rotation: enabling passive haptic feedback by aligning real and virtual objects in virtual reality
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All data generated or analysed during this study are included in this published article.Code Availibility:
Source code for the Unity build of the demonstration game and ’POWR’ itself can be found in the following repository: https://doi.org/10.5281/zenodo.7265808.Passive haptics have long been used to enhance the user’s experience in virtual reality (VR). However, creating props to be used in a virtual environment can be a complicated and lengthy process. Current research looks to create passive haptic props based on the layout of, or objects in, the user’s real environment. However, we identify three key limitations of current research. Firstly, procedural generation introduces many unknown variables into the design process, which complicates applying such techniques to scenarios requiring knowledge of the virtual environment’s layout ahead of time. Furthermore, such techniques limit the size and dimensions of the virtual space to that of the real space. Lastly, current research necessitates pre-scanning or real-time scanning of the user’s real environment, often requiring specialist equipment and expertise, thus limiting its generalisability. This research proposes Prop Oriented World Rotation, a technique that attempts to answer the aforementioned limitations and simplify the process of adding haptic feedback to VR applications. We implemented this technique in a demonstration game and give an overview of the steps taken to apply the technique in a real context. We analysed the demonstration system’s performance and conducted an initial user evaluation in three different physical environments. While our stress test of the system’s performance highlights the necessity for certain optimisations in complex environments, our initial user feedback suggests that users experienced a stronger sense of presence and feelings of safety in our passive haptics-enhanced environment. Hence, we conclude that our proposal has the potential to enhance experiences in VR with haptic feedback.Open Access funding enabled and organized by CAUL and its Member Institutions This research was conducted without any external funding
Citizenship and discomfort: Wearing (clothing) as an embodied act of citizenship
Get PDFThis article contributes to research on citizenship and belonging in the post-Brexit white East European migration to the UK. It explores wearing a garment as an act of citizenship and an embodied methodology. It is formed of two interrelated parts: the first presents the argument that wearing a particular garment at a specific spatio-temporal juncture can be considered an act of citizenship. The second part proposes wearing as an affective method in researching citizenship that has the potential to explore the sensory and emotional dimensions of (non)belonging. White embodiments and discomfort are two threads that connect the main arguments. The article builds on autoethnographic notes made after preparing for a job interview as a white East European woman wearing a Victorian male costume while travelling from East to South London in the wake of the General Election on 12 December 2019.Leverhulme Trust
MDEmoNet: A Multimodal Driver Emotion Recognition Network for Smart Cockpit
Get PDFThe automotive smart cockpit is an intelligent and connected in-vehicle consumer electronics product. It can provide a safe, efficient, comfortable, and enjoyable human-machine interaction experience. Emotion recognition technology can help the smart cockpit better understand the driver's needs and state, improve the driving experience, and enhance safety. Currently, driver emotion recognition faces some challenges, such as low accuracy and high latency. In this paper, we propose a multimodal driver emotion recognition model. To our best knowledge, it is the first time to improve the accuracy of driver emotion recognition by using facial video and driving behavior (including brake pedal force, vehicle Y-Axis position and Z-Axis position) as inputs and employing a multi-Task training approach. For verification, the proposed scheme is compared with some mainstream state-of-The-Art methods on the publicly available multimodal driver emotion dataset PPB-Emo.10.13039/501100001809-National Natural Science Foundation of China;
10.13039/100006190-Research and Development;
10.13039/501100003009-Science and Technology Development Fund
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