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High-throughput adaptive co-channel interference cancellation for edge devices using depthwise separable convolutions, quantization, and pruning
No full textCo-channel interference cancellation (CCI) is the process used to reduce interference from other signals using the same frequency channel, thereby enhancing the performance of wireless communication systems. An improvement to this approach is adaptive CCI, which reduces interference without relying on prior knowledge of the interfering signal characteristics. Recent work suggested using machine learning (ML) models for this purpose, but high-throughput ML solutions are still lacking, especially for edge devices with limited resources. This work explores the adaptation of U-Net Convolutional Neural Network models for high-throughput adaptive source separation. Our approach is established on architectural modifications, notably through quantization and the incorporation of depthwise separable convolution, to achieve a balance between computational efficiency and performance. Our results demonstrate that the proposed models achieve superior MSE scores when removing unknown interference sources from the signals while maintaining significantly lower computational complexity compared to baseline models. One of our proposed models is deeper and fully convolutional, while the other is shallower with a convolutional structure incorporating an LSTM. Depthwise separable convolution and quantization further reduce the memory footprint and computational demands, albeit with some performance tradeoffs. Specifically, applying depthwise separable convolutions to the model with the LSTM results in only a 0.72% degradation in MSE score while reducing MACs by 58.66%. For the fully convolutional model, we observe a 0.63% improvement in MSE score with even 61.10% fewer MACs. Additionally, the models exhibit excellent scalability on GPUs, with the fully convolutional model achieving the highest symbol rates (up to 800 103 symbol per second) at larger batch sizes. Overall, our findings underscore the feasibility of using optimized machine-learning models for interference cancellation in devices with limited resources.Co-channel interference cancellation (CCI) is the process used to reduce interference from other signals using the same frequency channel, thereby enhancing the performance of wireless communication systems. An improvement to this approach is adaptive CCI, which reduces interference without relying on prior knowledge of the interfering signal characteristics. Recent work suggested using machine learning (ML) models for this purpose, but high-throughput ML solutions are still lacking, especially for edge devices with limited resources. This work explores the adaptation of U-Net Convolutional Neural Network models for high-throughput adaptive source separation. Our approach is established on architectural modifications, notably through quantization and the incorporation of depthwise separable convolution, to achieve a balance between computational efficiency and performance. Our results demonstrate that the proposed models achieve superior MSE scores when removing unknown interference sources from the signals while maintaining significantly lower computational complexity compared to baseline models. One of our proposed models is deeper and fully convolutional, while the other is shallower with a convolutional structure incorporating an LSTM. Depthwise separable convolution and quantization further reduce the memory footprint and computational demands, albeit with some performance tradeoffs. Specifically, applying depthwise separable convolutions to the model with the LSTM results in only a 0.72% degradation in MSE score while reducing MACs by 58.66%. For the fully convolutional model, we observe a 0.63% improvement in MSE score with even 61.10% fewer MACs. Additionally, the models exhibit excellent scalability on GPUs, with the fully convolutional model achieving the highest symbol rates (up to 800 103 symbol per second) at larger batch sizes. Overall, our findings underscore the feasibility of using optimized machine-learning models for interference cancellation in devices with limited resources.A
Towards a multimodal approach for analysing interpreter's management of rapport challenge in onsite and video remote interpreting
No full textRecently, interpreters' management of rapport is increasingly being investigated. Yet little attention has been directed towards the role of the interpreter's non-verbal behaviour when managing rapport and to the influence of video mediated forms of interpreting on the use of non-verbal behaviour. Therefore, this study proposes a multimodal micro-interactional framework for analysing interpreters' management of rapport challenge in both onsite (OSI) and video remote interpreting (VRI) interaction. The paper introduces a multimodal coding scheme based on Spencer-Oatey's Rapport Management Theory (2008), which is then applied to a dataset of video recorded interpreter-mediated interactions to examine how interpreters employ verbal, paraverbal, and non-verbal resources to multimodally address rapport challenge. Data were collected from simulated interactions involving professional public service interpreters and role-players adopting the role of primary participants in a reception centre for asylum seekers. The findings reveal that in OSI interpreters use a wide range of non-verbal resources when conveying rapport challenges, whereas VRI imposes constraints on non-verbal communication, often necessitating more disruptive verbal strategies to manage rapport. The study underscores the importance of a multimodal approach to interpreting research, highlighting how non-verbal behaviours significantly contribute to the management of interpersonal relations in interpreter-mediated talk. (c) 2024 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.Recently, interpreters' management of rapport is increasingly being investigated. Yet little attention has been directed towards the role of the interpreter's non-verbal behaviour when managing rapport and to the influence of video mediated forms of interpreting on the use of non-verbal behaviour. Therefore, this study proposes a multimodal micro-interactional framework for analysing interpreters' management of rapport challenge in both onsite (OSI) and video remote interpreting (VRI) interaction. The paper introduces a multimodal coding scheme based on Spencer-Oatey's Rapport Management Theory (2008), which is then applied to a dataset of video recorded interpreter-mediated interactions to examine how interpreters employ verbal, paraverbal, and non-verbal resources to multimodally address rapport challenge. Data were collected from simulated interactions involving professional public service interpreters and role-players adopting the role of primary participants in a reception centre for asylum seekers. The findings reveal that in OSI interpreters use a wide range of non-verbal resources when conveying rapport challenges, whereas VRI imposes constraints on non-verbal communication, often necessitating more disruptive verbal strategies to manage rapport. The study underscores the importance of a multimodal approach to interpreting research, highlighting how non-verbal behaviours significantly contribute to the management of interpersonal relations in interpreter-mediated talk. (c) 2024 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.A
Working fluid and system optimisation of organic Rankine cycles via computer-aided molecular design : a review
No full textOrganic Rankine cycle (ORC) systems are a class of distributed power-generation systems that are suitable for the efficient conversion of low-to-medium temperature thermal energy to useful power. These versatile systems have significant potential to contribute in diverse ways to future clean and sustainable energy systems through, e.g., deployment for waste-heat recovery in industrial facilities, but also the utilisation of renewable-heat sources, thereby improving energy access and living standards, while reducing primary energy consumption and the associated emissions. The energetic and economic performance, but also environmental sustainability of ORC systems, all depend strongly on the working fluid employed, and therefore a significant effort has been made in recent years to select, but also to design novel working fluids for ORC systems. In this context, computer-aided molecular design (CAMD) techniques have emerged as highly promising approaches with which to explore the key role of working fluids, and present an opportunity, by focusing on the design of new eco-friendly fluids with low environmental footprints, to identify alternatives to traditional refrigerants with improved characteristics. In this review article, an overview of working-fluid and system optimisation methodologies that can be used for the design and operation of next-generation ORC systems is provided. With reference to wide-ranging applications from waste-heat recovery in industrial and automotive applications, to biomass, geothermal and solar-energy conversion and/or storage, this review represents a comprehensive, forward-looking exposition of the application of CAMD to the design of ORC technology.Organic Rankine cycle (ORC) systems are a class of distributed power-generation systems that are suitable for the efficient conversion of low-to-medium temperature thermal energy to useful power. These versatile systems have significant potential to contribute in diverse ways to future clean and sustainable energy systems through, e.g., deployment for waste-heat recovery in industrial facilities, but also the utilisation of renewable-heat sources, thereby improving energy access and living standards, while reducing primary energy consumption and the associated emissions. The energetic and economic performance, but also environmental sustainability of ORC systems, all depend strongly on the working fluid employed, and therefore a significant effort has been made in recent years to select, but also to design novel working fluids for ORC systems. In this context, computer-aided molecular design (CAMD) techniques have emerged as highly promising approaches with which to explore the key role of working fluids, and present an opportunity, by focusing on the design of new eco-friendly fluids with low environmental footprints, to identify alternatives to traditional refrigerants with improved characteristics. In this review article, an overview of working-fluid and system optimisation methodologies that can be used for the design and operation of next-generation ORC systems is provided. With reference to wide-ranging applications from waste-heat recovery in industrial and automotive applications, to biomass, geothermal and solar-energy conversion and/or storage, this review represents a comprehensive, forward-looking exposition of the application of CAMD to the design of ORC technology.A
Quality of prescribing and health-related quality of life in older adults : a narrative review with a special focus on patients with atrial fibrillation and multimorbidity
No full textPurpose: To summarise the association between potentially inappropriate prescribing (PIP) and health-related quality of life (HRQOL) in older adults, with a special focus on those with atrial fibrillation (AF) and multimorbidity, while exploring potential interventions to improve prescribing quality and their impact on HRQOL. Methods: A comprehensive search strategy was conducted in MEDLINE using the PubMed interface on August 16th, 2024, focusing on key terms related to “potentially inappropriate prescribing” and “quality of life”. Additionally, the reference lists of included studies were screened. Only studies utilising validated assessment tools for HRQOL or measuring global self-perceived health status were considered. Studies involving populations with an average age of ≥ 65 years were included.Results: Of the 1810 articles screened, 33 studies were included. The findings indicate that the quality of prescribing, independent of polypharmacy, may negatively influence HRQOL. The review identified a range of interventions aimed at improving prescribing quality among older adults, including pharmacist-driven, general practitioner-driven, and multidisciplinary approaches. Interventions were assessed among distinct population groups and specifically in residential care homes. While some interventions demonstrated improvements in prescribing quality, the overall evidence regarding their impact on HRQOL remains limited.Conclusion: The relationship between prescribing quality and HRQOL remains underexplored in older adults with AF and multimorbidity, despite the high prevalence of PIP. Effective pharmacotherapy should be coupled with a comprehensive assessment of patients' clinical and functional parameters, considering their HRQOL. Adopting a multidisciplinary, integrated, patient-centred approach is essential for sustainable and appropriate prescribing practices and may enhance HRQOL.Purpose: To summarise the association between potentially inappropriate prescribing (PIP) and health-related quality of life (HRQOL) in older adults, with a special focus on those with atrial fibrillation (AF) and multimorbidity, while exploring potential interventions to improve prescribing quality and their impact on HRQOL. Methods: A comprehensive search strategy was conducted in MEDLINE using the PubMed interface on August 16th, 2024, focusing on key terms related to “potentially inappropriate prescribing” and “quality of life”. Additionally, the reference lists of included studies were screened. Only studies utilising validated assessment tools for HRQOL or measuring global self-perceived health status were considered. Studies involving populations with an average age of ≥ 65 years were included.Results: Of the 1810 articles screened, 33 studies were included. The findings indicate that the quality of prescribing, independent of polypharmacy, may negatively influence HRQOL. The review identified a range of interventions aimed at improving prescribing quality among older adults, including pharmacist-driven, general practitioner-driven, and multidisciplinary approaches. Interventions were assessed among distinct population groups and specifically in residential care homes. While some interventions demonstrated improvements in prescribing quality, the overall evidence regarding their impact on HRQOL remains limited.Conclusion: The relationship between prescribing quality and HRQOL remains underexplored in older adults with AF and multimorbidity, despite the high prevalence of PIP. Effective pharmacotherapy should be coupled with a comprehensive assessment of patients' clinical and functional parameters, considering their HRQOL. Adopting a multidisciplinary, integrated, patient-centred approach is essential for sustainable and appropriate prescribing practices and may enhance HRQOL.A
Bursitis calcanei inferior : een zeldzame oorzaak van hielpijn
No full textBursitis calcanei inferior is een zeldzame oorzaak van hielpijn. Deze“de-novo-bursitis” komt het meest voor bij patiënten met reuma, maar kan ookhet gevolg zijn van mechanische overbelasting van de hiel. De diagnose wordtgesteld op beeldvorming door het aantonen van een onregelmatig afgelijndevochthoudende structuur in het vetkussentje van de hielBursitis calcanei inferior is een zeldzame oorzaak van hielpijn. Deze“de-novo-bursitis” komt het meest voor bij patiënten met reuma, maar kan ookhet gevolg zijn van mechanische overbelasting van de hiel. De diagnose wordtgesteld op beeldvorming door het aantonen van een onregelmatig afgelijndevochthoudende structuur in het vetkussentje van de hielA
Prospective REALITI-A study : 2-year real-world benefits of mepolizumab in severe asthma
No full textBackgroundMepolizumab, a monoclonal antibody targeting IL-5, is of proven clinical benefit in severe asthma; however, prospective, long-term, real-world data in severe asthma are required.Research QuestionWhat is the real-world benefit of 2 years of mepolizumab treatment in severe asthma?Study Design and MethodsREALITI-A was a 2-year, international, prospective study enrolling adults with asthma on newly initiated mepolizumab 100 mg subcutaneously (physician decision). Outcomes in the 1-year premepolizumab vs 2-year follow-up periods included rates of clinically significant asthma exacerbations (CSEs) (deterioration requiring systemic corticosteroids and/or emergency department [ED] visit/hospitalization), exacerbations requiring ED visit/hospitalization, exacerbations requiring hospitalization, proportion of patients with no exacerbations, median daily maintenance oral corticosteroids (mOCSs) dose, proportion of patients discontinuing mOCSs completely, Asthma Control Questionnaire-5 score, FEV1, and adverse events (AEs).ResultsAfter 2 years’ follow-up, 73% of patients (599 of 822) had no record of mepolizumab discontinuation. During the 2-year follow-up vs premepolizumab period (N = 822), rates of CSEs, exacerbations requiring ED visit/hospitalization, or hospitalization only were reduced by 74%, 79%, and 73%, respectively (odds ratio for no CSEs, 10.0; 95% CI, 7.55- 13.25). Median daily mOCS dose decreased from 10.0 (quartile 1, 5.0; quartile 3, 14.7) mg at week 0 (n = 297) to 0.0 (quartile 1, 0.0; quartile 3, 5.0) mg at weeks 101 to 104 (n = 168), and the proportion of patients discontinuing mOCS increased progressively to 43% at 1 year and 57% at 2 years. There was a 1.53-point reduction in Asthma Control Questionnaire-5 scores from baseline at 2 years. At months 21 to 24, least square mean FEV1 improved by 142 mL from baseline. Ninety (11%) and 7 (< 1%) patients experienced mepolizumab-related AEs and serious AEs during the follow-up period, respectively.InterpretationIn patients with severe asthma, real-world mepolizumab treatment for 2 years was well tolerated and was associated with sustained reductions in exacerbations and progressive reductions in mOCS use.BackgroundMepolizumab, a monoclonal antibody targeting IL-5, is of proven clinical benefit in severe asthma; however, prospective, long-term, real-world data in severe asthma are required.Research QuestionWhat is the real-world benefit of 2 years of mepolizumab treatment in severe asthma?Study Design and MethodsREALITI-A was a 2-year, international, prospective study enrolling adults with asthma on newly initiated mepolizumab 100 mg subcutaneously (physician decision). Outcomes in the 1-year premepolizumab vs 2-year follow-up periods included rates of clinically significant asthma exacerbations (CSEs) (deterioration requiring systemic corticosteroids and/or emergency department [ED] visit/hospitalization), exacerbations requiring ED visit/hospitalization, exacerbations requiring hospitalization, proportion of patients with no exacerbations, median daily maintenance oral corticosteroids (mOCSs) dose, proportion of patients discontinuing mOCSs completely, Asthma Control Questionnaire-5 score, FEV1, and adverse events (AEs).ResultsAfter 2 years’ follow-up, 73% of patients (599 of 822) had no record of mepolizumab discontinuation. During the 2-year follow-up vs premepolizumab period (N = 822), rates of CSEs, exacerbations requiring ED visit/hospitalization, or hospitalization only were reduced by 74%, 79%, and 73%, respectively (odds ratio for no CSEs, 10.0; 95% CI, 7.55- 13.25). Median daily mOCS dose decreased from 10.0 (quartile 1, 5.0; quartile 3, 14.7) mg at week 0 (n = 297) to 0.0 (quartile 1, 0.0; quartile 3, 5.0) mg at weeks 101 to 104 (n = 168), and the proportion of patients discontinuing mOCS increased progressively to 43% at 1 year and 57% at 2 years. There was a 1.53-point reduction in Asthma Control Questionnaire-5 scores from baseline at 2 years. At months 21 to 24, least square mean FEV1 improved by 142 mL from baseline. Ninety (11%) and 7 (< 1%) patients experienced mepolizumab-related AEs and serious AEs during the follow-up period, respectively.InterpretationIn patients with severe asthma, real-world mepolizumab treatment for 2 years was well tolerated and was associated with sustained reductions in exacerbations and progressive reductions in mOCS use.A
Nudging in nightlife : a scoping review of choice architecture interventions in nightlife and similar settings
No full textAlthough nightlife is valued for diverse reasons like socializing and unwinding, it is also a setting where various undesirable activities, such as substance abuse, public urination, or harassment, frequently occur. Traditional prevention measures in this context, such as regulations or information campaigns, often assume that nightlife visitors make fully rational decisions. However, given the limitations of human rationality, several scholars have argued to incorporate behavioral science insights into such prevention policies (e.g., Pogarsky & Herman, 2019). Indeed, nudging or the attempt to influence people's judgment, choice, or behavior by leveraging cognitive biases that hinder rational decision-making (Thaler & Sunstein, 2008, 2021), has proven to be an effective policy tool in many areas of public interest, including healthcare. The behavioral approach may be particularly relevant in nightlife prevention efforts, given that the typical nightlife environment often impairs rational and conscious thinking (e.g., through intoxication), causing individuals to rely more on intuitive and unconscious decision-making (Giancola et al., 2010). However, due to the unique nature of nightlife environments, researchers and policymakers cannot assume that insights from nudging interventions in other contexts can be directly generalized to address certain behaviors in nightlife (Sunstein, 2017).This scoping review aims to explore the existing literature on nudging interventions in nightlife settings, providing an overview of implemented choice architecture interventions and their respective impacts. The review includes academic contributions on the application of nudging in both nightlife settings (e.g., near or in bars, pubs, and clubs) and contexts closely resembling nightlife environments, like festivals, music events, and other comparable gatherings. Furthermore, we use the recently updated BERRY-framework, a taxonomy of choice architecture techniques (Münscher, 2024), to structure our search and categorize the various applications of nudging. The review synthesizes the impact and characteristics of nudges implemented in nightlife or similar settings, including the targeted population, decision-making process or behavior addressed, desired outcomes, choice architecture techniques employed, cognitive biases leveraged, and the intervention format (e.g., leaflet, sticker, sound, etc.). In this presentation, the research design of the scoping review will be discussed, along with some preliminary results.Although nightlife is valued for diverse reasons like socializing and unwinding, it is also a setting where various undesirable activities, such as substance abuse, public urination, or harassment, frequently occur. Traditional prevention measures in this context, such as regulations or information campaigns, often assume that nightlife visitors make fully rational decisions. However, given the limitations of human rationality, several scholars have argued to incorporate behavioral science insights into such prevention policies (e.g., Pogarsky & Herman, 2019). Indeed, nudging or the attempt to influence people's judgment, choice, or behavior by leveraging cognitive biases that hinder rational decision-making (Thaler & Sunstein, 2008, 2021), has proven to be an effective policy tool in many areas of public interest, including healthcare. The behavioral approach may be particularly relevant in nightlife prevention efforts, given that the typical nightlife environment often impairs rational and conscious thinking (e.g., through intoxication), causing individuals to rely more on intuitive and unconscious decision-making (Giancola et al., 2010). However, due to the unique nature of nightlife environments, researchers and policymakers cannot assume that insights from nudging interventions in other contexts can be directly generalized to address certain behaviors in nightlife (Sunstein, 2017).This scoping review aims to explore the existing literature on nudging interventions in nightlife settings, providing an overview of implemented choice architecture interventions and their respective impacts. The review includes academic contributions on the application of nudging in both nightlife settings (e.g., near or in bars, pubs, and clubs) and contexts closely resembling nightlife environments, like festivals, music events, and other comparable gatherings. Furthermore, we use the recently updated BERRY-framework, a taxonomy of choice architecture techniques (Münscher, 2024), to structure our search and categorize the various applications of nudging. The review synthesizes the impact and characteristics of nudges implemented in nightlife or similar settings, including the targeted population, decision-making process or behavior addressed, desired outcomes, choice architecture techniques employed, cognitive biases leveraged, and the intervention format (e.g., leaflet, sticker, sound, etc.). In this presentation, the research design of the scoping review will be discussed, along with some preliminary results.C
