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Introduction Prospective double-blind placebo-controlled randomized clinical trials (RCTs) are considered standard for the proof of the efficacy of oncologic therapies. Molecular methods have provided new insights into tumor biology and led to the development of targeted therapies. Due to the increasing complexity of molecular tumor characteristics and of the individuality of specific anti-tumor immune reactivity, RCTs are unfortunately only of limited use. Areas covered The historical methods of drug research and approval and the related practices of reimbursement by statutory and private health insurance companies are being questioned. New, innovative methods for the documentation of evidence in personalized medicine will be addressed. Possible perspectives and new approaches are discussed, in particular with regard to glioblastoma. Expert opinion Highly specialized translational oncology groups like the IOZK can contribute to medical progress and quick transfer 'from bench to bedside.' Their contribution should be acknowledged and taken into account more strongly in the development of guidelines and the reimbursement of therapy costs. Methodological plurality should be encouraged.

Introduction Prospective double-blind placebo-controlled randomized clinical trials (RCTs) are considered standard for the proof of the efficacy of oncologic therapies. Molecular methods have provided new insights into tumor biology and led to the development of targeted therapies. Due to the increasing complexity of molecular tumor characteristics and of the individuality of specific anti-tumor immune reactivity, RCTs are unfortunately only of limited use. Areas covered The historical methods of drug research and approval and the related practices of reimbursement by statutory and private health insurance companies are being questioned. New, innovative methods for the documentation of evidence in personalized medicine will be addressed. Possible perspectives and new approaches are discussed, in particular with regard to glioblastoma. Expert opinion Highly specialized translational oncology groups like the IOZK can contribute to medical progress and quick transfer 'from bench to bedside.' Their contribution should be acknowledged and taken into account more strongly in the development of guidelines and the reimbursement of therapy costs. Methodological plurality should be encouraged.

Objective: The Swedish Rheumatology Quality Register has implemented an internet-based method (PER) for registering patient-recorded outcome measures. The aim of this study was to compare the agreement between visual analogue scales (VASs) reported via PER and clinic-based reporting using paper forms.Methods: In a cross-sectional study (70 patients), the results of 79 registrations of VASs for global health, pain, and fatigue from PER were compared with corresponding clinic-based paper registrations. For patients with polyarthritis, 28-joint count Disease Activity Scores (DAS28) were computed. Patients with axial disease also completed Bath Ankylosing Spondylitis Disease Activity Index and Functional Index (BASDAI and BASFI) questionnaires. Mean differences and intraclass correlation coefficients (ICCs) were calculated. Agreement was visualized using Bland-Altman plots.Results: No statistically significant differences in VASs were found comparing PER and paper forms for VAS Global, VAS Pain, and VAS Fatigue (p=0.295, 0.463, and 0.288, respectively). ICCs for VAS Global, Pain, and Fatigue ranged from 0.889 to 0.952, indicating excellent agreement. Bland-Altman plots for VAS did not show any proportional bias. The mean difference for DAS28 calculated by VASs from paper vs PER was -0.02 (n=65, p =0.660), and the mean difference for BASDAI was 0.04 (n=11, p =0.742). ICCs for DAS28 and BASDAI were 0.962 and 0.985, respectively. Of the participating patients, 60% preferred PER.Conclusion: Internet-based reporting for patient-reported outcomes in a clinical setting resulted in similar data for VASs and corresponding disease activity scores to clinic-based reporting on paper forms.

Objective: The Swedish Rheumatology Quality Register has implemented an internet-based method (PER) for registering patient-recorded outcome measures. The aim of this study was to compare the agreement between visual analogue scales (VASs) reported via PER and clinic-based reporting using paper forms.Methods: In a cross-sectional study (70 patients), the results of 79 registrations of VASs for global health, pain, and fatigue from PER were compared with corresponding clinic-based paper registrations. For patients with polyarthritis, 28-joint count Disease Activity Scores (DAS28) were computed. Patients with axial disease also completed Bath Ankylosing Spondylitis Disease Activity Index and Functional Index (BASDAI and BASFI) questionnaires. Mean differences and intraclass correlation coefficients (ICCs) were calculated. Agreement was visualized using Bland-Altman plots.Results: No statistically significant differences in VASs were found comparing PER and paper forms for VAS Global, VAS Pain, and VAS Fatigue (p=0.295, 0.463, and 0.288, respectively). ICCs for VAS Global, Pain, and Fatigue ranged from 0.889 to 0.952, indicating excellent agreement. Bland-Altman plots for VAS did not show any proportional bias. The mean difference for DAS28 calculated by VASs from paper vs PER was -0.02 (n=65, p =0.660), and the mean difference for BASDAI was 0.04 (n=11, p =0.742). ICCs for DAS28 and BASDAI were 0.962 and 0.985, respectively. Of the participating patients, 60% preferred PER.Conclusion: Internet-based reporting for patient-reported outcomes in a clinical setting resulted in similar data for VASs and corresponding disease activity scores to clinic-based reporting on paper forms.

Objective: The Swedish Rheumatology Quality Register has implemented an internet-based method (PER) for registering patient-recorded outcome measures. The aim of this study was to compare the agreement between visual analogue scales (VASs) reported via PER and clinic-based reporting using paper forms.Methods: In a cross-sectional study (70 patients), the results of 79 registrations of VASs for global health, pain, and fatigue from PER were compared with corresponding clinic-based paper registrations. For patients with polyarthritis, 28-joint count Disease Activity Scores (DAS28) were computed. Patients with axial disease also completed Bath Ankylosing Spondylitis Disease Activity Index and Functional Index (BASDAI and BASFI) questionnaires. Mean differences and intraclass correlation coefficients (ICCs) were calculated. Agreement was visualized using Bland-Altman plots.Results: No statistically significant differences in VASs were found comparing PER and paper forms for VAS Global, VAS Pain, and VAS Fatigue (p=0.295, 0.463, and 0.288, respectively). ICCs for VAS Global, Pain, and Fatigue ranged from 0.889 to 0.952, indicating excellent agreement. Bland-Altman plots for VAS did not show any proportional bias. The mean difference for DAS28 calculated by VASs from paper vs PER was -0.02 (n=65, p =0.660), and the mean difference for BASDAI was 0.04 (n=11, p =0.742). ICCs for DAS28 and BASDAI were 0.962 and 0.985, respectively. Of the participating patients, 60% preferred PER.Conclusion: Internet-based reporting for patient-reported outcomes in a clinical setting resulted in similar data for VASs and corresponding disease activity scores to clinic-based reporting on paper forms.

Objective: The Swedish Rheumatology Quality Register has implemented an internet-based method (PER) for registering patient-recorded outcome measures. The aim of this study was to compare the agreement between visual analogue scales (VASs) reported via PER and clinic-based reporting using paper forms.Methods: In a cross-sectional study (70 patients), the results of 79 registrations of VASs for global health, pain, and fatigue from PER were compared with corresponding clinic-based paper registrations. For patients with polyarthritis, 28-joint count Disease Activity Scores (DAS28) were computed. Patients with axial disease also completed Bath Ankylosing Spondylitis Disease Activity Index and Functional Index (BASDAI and BASFI) questionnaires. Mean differences and intraclass correlation coefficients (ICCs) were calculated. Agreement was visualized using Bland-Altman plots.Results: No statistically significant differences in VASs were found comparing PER and paper forms for VAS Global, VAS Pain, and VAS Fatigue (p=0.295, 0.463, and 0.288, respectively). ICCs for VAS Global, Pain, and Fatigue ranged from 0.889 to 0.952, indicating excellent agreement. Bland-Altman plots for VAS did not show any proportional bias. The mean difference for DAS28 calculated by VASs from paper vs PER was -0.02 (n=65, p =0.660), and the mean difference for BASDAI was 0.04 (n=11, p =0.742). ICCs for DAS28 and BASDAI were 0.962 and 0.985, respectively. Of the participating patients, 60% preferred PER.Conclusion: Internet-based reporting for patient-reported outcomes in a clinical setting resulted in similar data for VASs and corresponding disease activity scores to clinic-based reporting on paper forms.

Objective: The Swedish Rheumatology Quality Register has implemented an internet-based method (PER) for registering patient-recorded outcome measures. The aim of this study was to compare the agreement between visual analogue scales (VASs) reported via PER and clinic-based reporting using paper forms.Methods: In a cross-sectional study (70 patients), the results of 79 registrations of VASs for global health, pain, and fatigue from PER were compared with corresponding clinic-based paper registrations. For patients with polyarthritis, 28-joint count Disease Activity Scores (DAS28) were computed. Patients with axial disease also completed Bath Ankylosing Spondylitis Disease Activity Index and Functional Index (BASDAI and BASFI) questionnaires. Mean differences and intraclass correlation coefficients (ICCs) were calculated. Agreement was visualized using Bland-Altman plots.Results: No statistically significant differences in VASs were found comparing PER and paper forms for VAS Global, VAS Pain, and VAS Fatigue (p=0.295, 0.463, and 0.288, respectively). ICCs for VAS Global, Pain, and Fatigue ranged from 0.889 to 0.952, indicating excellent agreement. Bland-Altman plots for VAS did not show any proportional bias. The mean difference for DAS28 calculated by VASs from paper vs PER was -0.02 (n=65, p =0.660), and the mean difference for BASDAI was 0.04 (n=11, p =0.742). ICCs for DAS28 and BASDAI were 0.962 and 0.985, respectively. Of the participating patients, 60% preferred PER.Conclusion: Internet-based reporting for patient-reported outcomes in a clinical setting resulted in similar data for VASs and corresponding disease activity scores to clinic-based reporting on paper forms.

The release of RNA-containing extracellular vesicles (EV) into the extracellular milieu has been demonstrated in a multitude of different in vitro cell systems and in a variety of body fluids. RNA-containing EV are in the limelight for their capacity to communicate genetically encoded messages to other cells, their suitability as candidate biomarkers for diseases, and their use as therapeutic agents. Although EV-RNA has attracted enormous interest from basic researchers, clinicians, and industry, we currently have limited knowledge on which mechanisms drive and regulate RNA incorporation into EV and on how RNA-encoded messages affect signalling processes in EV-targeted cells. Moreover, EV-RNA research faces various technical challenges, such as standardisation of EV isolation methods, optimisation of methodologies to isolate and characterise minute quantities of RNA found in EV, and development of approaches to demonstrate functional transfer of EV-RNA in vivo. These topics were discussed at the 2015 EV-RNA workshop of the International Society for Extracellular Vesicles. This position paper was written by the participants of the workshop not only to give an overview of the current state of knowledge in the field, but also to clarify that our incomplete knowledge - of the nature of EV(-RNA)s and of how to effectively and reliably study them - currently prohibits the implementation of gold standards in EV-RNA research. In addition, this paper creates awareness of possibilities and limitations of currently used strategies to investigate EV-RNA and calls for caution in interpretation of the obtained data.

Extracellular vesicles (EVs), such as exosomes and microvesicles, are released by different cell types and participate in physiological and pathophysiological processes. EVs mediate intercellular communication as cell-derived extracellular signalling organelles that transmit specific information from their cell of origin to their target cells. As a result of these properties, EVs of defined cell types may serve as novel tools for various therapeutic approaches, including (a) anti-tumour therapy, (b) pathogen vaccination, (c) immune-modulatory and regenerative therapies and (d) drug delivery. The translation of EVs into clinical therapies requires the categorization of EV-based therapeutics in compliance with existing regulatory frameworks. As the classification defines subsequent requirements for manufacturing, quality control and clinical investigation, it is of major importance to define whether EVs are considered the active drug components or primarily serve as drug delivery vehicles. For an effective and particularly safe translation of EV-based therapies into clinical practice, a high level of cooperation between researchers, clinicians and competent authorities is essential. In this position statement, basic and clinical scientists, as members of the International Society for Extracellular Vesicles (ISEV) and of the European Cooperation in Science and Technology (COST) program of the European Union, namely European Network on Microvesicles and Exosomes in Health and Disease (ME-HaD), summarize recent developments and the current knowledge of EV-based therapies. Aspects of safety and regulatory requirements that must be considered for pharmaceutical manufacturing and clinical application are highlighted. Production and quality control processes are discussed. Strategies to promote the therapeutic application of EVs in future clinical studies are addressed.

IntroductionInternet-based psychological treatments for depression have been around for more than 20 years. There has been a continuous line of research with new research questions being asked and studies conducted.Areas coveredIn this paper, the author reviews studies with a focus on papers published from 2020 and onwards based on a Medline and Scopus search. Internet-based cognitive behavior therapy (ICBT) programs have been developed and tested for adolescents, older adults, immigrant groups and to handle a societal crisis (e.g. COVID-19). ICBT works in regular clinical settings and long-term effects can be obtained. Studies on different treatment orientations and approaches such as acceptance commitment therapy, unified protocol, and tailored treatments have been conducted. Effects on quality-of-life measures, knowledge acquisition and ecological momentary assessment as a research tool have been reported. Factorial design trials and individual patient data meta-analysis are increasingly used in association with internet intervention research. Finally, prediction studies and recent advances in artificial intelligence are mentioned.Expert opinionInternet-delivered treatments are effective, in particular if therapist guidance is provided. More target groups have been covered but there are many remaining challenges including how new tools like artificial intelligence will be used when treating depression., Funding Agencies|Linkoping University

The present paper investigates Cox-Ingersoll-Ross (CIR) processes of dimension less than 1, with a focus on obtaining an equation of a new type including local times for the square root of the CIR process. To derive this equation, we utilize the fact that non-negative diffusion processes can be obtained by the transformation of time and scale of a certain reflected Brownian motion. The equation mentioned above turns out to contain a term characterized by the local time of the corresponding reflected Brownian motion. Additionally, we establish a new connection between low-dimensional CIR processes and reflected Ornstein-Uhlenbeck (ROU) processes, providing a new representation of Skorokhod reflection functions.

For heat resistant alloys, long-term structural stability at high temperatures is a critical issue for alloy design and applications. In this paper, the long-term creep behaviours and structural stabilities of six heat resistant high Ni alloys and austenitic stainless steels have been studied. The longest creep rupture life is up to 359 283 hours. High Ni and Cr alloys show a good combination of high creep and oxidation resistances. Precipitation of nano MX particles with a very low growth rate improves long-term creep resistance at high temperatures. Long-term stable multiple nanoprecipitates of MX, Cu-rich, Laves and M23C6 phases can greatly contribute to the creep strength. Low Ni austenitic stainless steels show comparatively low oxidation and creep resistances. It was first found that at 800 & DEG;C, Cr2N could form in the low Ni steel with a long-term crept by the absorption of nitrogen from the air into the matrix.

In most western legal systems, only the fact-finder (judge or jury) is entrusted to make the ultimate decision in a criminal case. A forensic expert can help the fact-finder by opining on the weight of the forensic evidence given the hypotheses relevant to the case, but is not qualified to give an opinion about the ultimate question(s). When the question is reduced to two simple hypotheses, a Bayes Factor can express the expert's opinion about the extent to which the forensic evidence favours each hypothesis. This paper addresses the situation in which one or both of the hypotheses are composite, that is, embrace more than one possibility. It offers an interval of Bayes Factors, and shows that the proposed interval includes those values, and only those values, of the Bayes Factor supported by possible beliefs of the fact-finder. Shoe prints, tool marks and DNA are discussed in this light if the hypotheses used in the Bayes Factor are composite., Funding Agencies|Qatar National Library

In this paper, the high-temperature constitutive behaviour of an additively manufactured ductile nickel-based superalloy is investigated and modelled, with application to thermomechanical fatigue, low-cycle fatigue and creep conditions at temperatures up to 800∘800∘C. Thermomechanical fatigue tests have been performed on smooth specimens in both in-phase and out-of-phase conditions at a temperature range of 100−800∘100−800∘C, and creep tests at 625∘625∘C, 700∘700∘C, 750∘750∘C and 800∘800∘C. Additionally, low-cycle fatigue tests at different strain ranges and load ratios have been performed at 700∘700, Funding Agencies|Linkoping University and Siemens Energy AB

Increased demand for actionable knowledge in operations- and supply chain management has fuelled the interest in collaborative, action-oriented research design as well as modes of theorising that generate adaptable and actionable frameworks. Whilst action research (AR) design as well as middle-range theories (MRT) offer guiding principles herein, they are researcher centric in nature. It is taken for granted that practitioners that enter such an endeavour have a certain level of knowledge or experience prior to the initial stages of formalising the research problem. Practitioners in non-academic, operations management-intensive industries or craftsmanship-based industries, such as construction or carpeting (often in the SME range) are often neither prepared nor equipped with the principles necessary to convey their managerial challenges into collaborative research design. This risk limiting or even hindering altogether such participation. This paper elaborates on combining the logic of AR and MRT. By conceptualising a preparatory phase for initiating practitioner engagement, complementing the conventional AR cycle, a four-step approach is presented: (1) Identifying a joint interest; (2) Teaching - Awakening interest in the topic through MRT frameworks; (3) Accepting buy-in to the AR cycle and determining the problem; and (4) Proposing MRT frameworks for analysis and entering the traditional AR cycle.

The use of public works programs to combat economic recessions is a recurring issue. In this paper we conducted an empirical analysis covering 160 countries (out of which 43 were retained) over 30 years, to determine to what extent it has been possible in the past to deploy PPPs as part of a wider countercyclical policy. The main criterion used in the analyses performed is the comparison between numbers and values of PPP projects reaching financial close during recessions and those outside a recession. The results are disappointing: only a handful of European countries have been successful. The only sensible approach, that works only in some developed nations, would be increasing the number of PPP projects while maintaining project size. This research contributes to the understanding of PPP adoption during economic recessions, sheds light on the different strategies of developed and developing countries, and emphasizes the challenges and opportunities associated with implementing countercyclical PPP policies. These insights can inform policymakers, practitioners, and researchers in their decision-making processes and contribute to the advancement of knowledge in the field of PPP project procurement and management.

The Something Awful Let’s Play subforum is widely acknowledged as the birthplace of the Let’s Play (LP) media phenomenon. LPs typically involve people recording themselves playing games while providing commentary. LPs are an important media form in themselves as well as being an important antecedent to many contemporary and popular media forms such as live streaming, esports and speed-running. An examination of the Something Awful LP subforum can contribute to an understanding of the origins of LPs and the community that created them. In this paper, we report on a study of the Something Awful LP subforum and describe the kinds of engagement the community participates in the top threads, as well as looking to see if there are specific individuals responsible for guiding the subforum overall. We collected data from the thousands of public threads posted in the LP subforum, from its inception in 2007 to the end of 2020. The analysis of these postings presented in this paper draws on previous understandings of the behavioral roles, forms of engagement, and policing of practices that often occur on internet forums as part of the regulation and organization of associated online communities. Our results show that the LP subforum was not dominated by a small minority of users that dictated the community’s LP posting, recording and commentary practices, and that the content of the specific threads was much more important in determining what forms of LPs became popular.

The emergence of autonomous vehicles is attracting intense scrutiny for the transformative effects it may have on urban infrastructures and planning systems. Much of this scrutiny, though, has arguably focused on driverless passenger cars designed to operate on conventional carriageways. In this paper, we argue the car-centric vision of autonomous mobility limits our ability to identify and respond to the challenges posed by a suite of alternative vehicles found in hallways, footpaths, and (sub)urban precincts. We address this problem by presenting a typological description of autonomous vehicles beyond the driverless car. The paper describes their configuration and performance, identifies the spaces and use-cases they are associated with, and gestures to the challenges they raise for urban environments. The paper synthesises the observations generated through the typology into a set of complex questions demonstrated through the scenarioof a self-driving pod providing passenger transport at a university campus. It shows that, with a broad range of autonomous vehicles already operating in our cities, we need finer-grained analyses of how they are integrated into shared pedestrian spaces. The typology it offers provides a platform for this research by enhancing our comprehension of autonomous mobility forms, functions, and spaces. This will support further mobilities research on the proccesses and outcomes of urban experiments with autonomous systems.

The emergence of autonomous vehicles is attracting intense scrutiny for the transformative effects it may have on urban infrastructures and planning systems. Much of this scrutiny, though, has arguably focused on driverless passenger cars designed to operate on conventional carriageways. In this paper, we argue the car-centric vision of autonomous mobility limits our ability to identify and respond to the challenges posed by a suite of alternative vehicles found in hallways, footpaths, and (sub)urban precincts. We address this problem by presenting a typological description of autonomous vehicles beyond the driverless car. The paper describes their configuration and performance, identifies the spaces and use-cases they are associated with, and gestures to the challenges they raise for urban environments. The paper synthesises the observations generated through the typology into a set of complex questions demonstrated through the scenarioof a self-driving pod providing passenger transport at a university campus. It shows that, with a broad range of autonomous vehicles already operating in our cities, we need finer-grained analyses of how they are integrated into shared pedestrian spaces. The typology it offers provides a platform for this research by enhancing our comprehension of autonomous mobility forms, functions, and spaces. This will support further mobilities research on the proccesses and outcomes of urban experiments with autonomous systems.

This paper proposes a semi-analytical method for the time-dependent reliability assessment of steel pipelines exposed to localized corrosion. The failure modes considered in this paper include corrosion perforation and local burst due to the growth of defect depth and length. For a short pipeline, a spatial-temporal Poisson model is used to describe the occurrence of corrosion defects. The method is further generalized for the reliability assessment of a long pipeline, which is treated as a series system consisting of different segments. The spatial correlation of the behaviour of adjacent segments is taken into account, and is modeled by the Nataf transformation method. An example is presented to demonstrate the applicability of the proposed method. Analytical results show that the reliability of a short pipeline can be significantly underestimated if the assessment method for a single corrosion defect is used instead. For a long pipeline, the failure probability is smaller in the presence of a stronger spatial correlation between different segments, suggesting that the manufacturing procedure and assembling practice of different segments should be synchronized with each other in order to improve pipeline reliability.

The emergence of autonomous vehicles is attracting intense scrutiny for the transformative effects it may have on urban infrastructures and planning systems. Much of this scrutiny, though, has arguably focused on driverless passenger cars designed to operate on conventional carriageways. In this paper, we argue the car-centric vision of autonomous mobility limits our ability to identify and respond to the challenges posed by a suite of alternative vehicles found in hallways, footpaths, and (sub)urban precincts. We address this problem by presenting a typological description of autonomous vehicles beyond the driverless car. The paper describes their configuration and performance, identifies the spaces and use-cases they are associated with, and gestures to the challenges they raise for urban environments. The paper synthesises the observations generated through the typology into a set of complex questions demonstrated through the scenarioof a self-driving pod providing passenger transport at a university campus. It shows that, with a broad range of autonomous vehicles already operating in our cities, we need finer-grained analyses of how they are integrated into shared pedestrian spaces. The typology it offers provides a platform for this research by enhancing our comprehension of autonomous mobility forms, functions, and spaces. This will support further mobilities research on the proccesses and outcomes of urban experiments with autonomous systems.

Artificial intelligence (AI) has been widely used in robotics, automation, finance, healthcare, etc. However, using AI for decision-making in sustainable product lifecycle operations is still challenging. One major challenge relates to the scarcity and uncertainties of data across the product lifecycle. This paper aims to develop a method that can adopt the most suitable AI techniques to support decision-making for sustainable operations based on the available lifecycle data. It identifies the key lifecycle stages in which AI, especially reinforcement learning (RL), can support decision-making. Then, a generalised procedure of using RL for decision support is proposed based on available lifecycle data, such as operation and maintenance data. The method has been validated in a case study of an international vehicle manufacturer, combined with modelling and simulation. The case study demonstrates the effectiveness of the method and identifies that RL is the current most appropriate method for maintenance scheduling based on limited available lifecycle data. This paper contributes to knowledge by demonstrating an empirically grounded industrial case using RL to optimise decision-making for improved product lifecycle sustainability by effectively prolonging the product lifetime and reducing environmental impact., Funding Agencies|VinnovaVinnova [2017-01649]

Artificial intelligence (AI) has been widely used in robotics, automation, finance, healthcare, etc. However, using AI for decision-making in sustainable product lifecycle operations is still challenging. One major challenge relates to the scarcity and uncertainties of data across the product lifecycle. This paper aims to develop a method that can adopt the most suitable AI techniques to support decision-making for sustainable operations based on the available lifecycle data. It identifies the key lifecycle stages in which AI, especially reinforcement learning (RL), can support decision-making. Then, a generalised procedure of using RL for decision support is proposed based on available lifecycle data, such as operation and maintenance data. The method has been validated in a case study of an international vehicle manufacturer, combined with modelling and simulation. The case study demonstrates the effectiveness of the method and identifies that RL is the current most appropriate method for maintenance scheduling based on limited available lifecycle data. This paper contributes to knowledge by demonstrating an empirically grounded industrial case using RL to optimise decision-making for improved product lifecycle sustainability by effectively prolonging the product lifetime and reducing environmental impact., Funding Agencies|VinnovaVinnova [2017-01649]

Artificial intelligence (AI) has been widely used in robotics, automation, finance, healthcare, etc. However, using AI for decision-making in sustainable product lifecycle operations is still challenging. One major challenge relates to the scarcity and uncertainties of data across the product lifecycle. This paper aims to develop a method that can adopt the most suitable AI techniques to support decision-making for sustainable operations based on the available lifecycle data. It identifies the key lifecycle stages in which AI, especially reinforcement learning (RL), can support decision-making. Then, a generalised procedure of using RL for decision support is proposed based on available lifecycle data, such as operation and maintenance data. The method has been validated in a case study of an international vehicle manufacturer, combined with modelling and simulation. The case study demonstrates the effectiveness of the method and identifies that RL is the current most appropriate method for maintenance scheduling based on limited available lifecycle data. This paper contributes to knowledge by demonstrating an empirically grounded industrial case using RL to optimise decision-making for improved product lifecycle sustainability by effectively prolonging the product lifetime and reducing environmental impact., Funding Agencies|VinnovaVinnova [2017-01649]

Waste management in the Architecture, Engineering and Construction (AEC) industry has been a major research topic owing to the AEC industry being one of the top contributors of waste generation. However, research has primarily focused on new build and has neglected refurbishment projects which become relevant due to an aging building stock in Sweden and Europe. Various actors are involved in refurbishment projects which makes it important to study each actor as well as tensions between them. By using a service ecosystem perspective and relying on 38 interviews, this paper aims to investigate tensions and barriers between actors within the service ecosystem of CDW for refurbishment projects in Sweden. Based on the results, spatial barriers are the most mentioned barrier which also create the highest number of tensions between project and contractor mother firm, subcontractors, waste recycling firms and society/citizens. The majority of the tensions are found between projects and the contractor mother firms, followed by tensions between projects and clients and projects and subcontractors. Unlike previous studies investigating only one of the actors waste management practices, this paper contributes by investigating the interactions between seven different actors which is important for improving waste management practices in refurbishment projects., Funding Agencies|Mistra Closing the Loop, the Foundation for Strategic Environmental Research [160026]

Artificial intelligence (AI) has been widely used in robotics, automation, finance, healthcare, etc. However, using AI for decision-making in sustainable product lifecycle operations is still challenging. One major challenge relates to the scarcity and uncertainties of data across the product lifecycle. This paper aims to develop a method that can adopt the most suitable AI techniques to support decision-making for sustainable operations based on the available lifecycle data. It identifies the key lifecycle stages in which AI, especially reinforcement learning (RL), can support decision-making. Then, a generalised procedure of using RL for decision support is proposed based on available lifecycle data, such as operation and maintenance data. The method has been validated in a case study of an international vehicle manufacturer, combined with modelling and simulation. The case study demonstrates the effectiveness of the method and identifies that RL is the current most appropriate method for maintenance scheduling based on limited available lifecycle data. This paper contributes to knowledge by demonstrating an empirically grounded industrial case using RL to optimise decision-making for improved product lifecycle sustainability by effectively prolonging the product lifetime and reducing environmental impact., Funding Agencies|VinnovaVinnova [2017-01649]

Waste management in the Architecture, Engineering and Construction (AEC) industry has been a major research topic owing to the AEC industry being one of the top contributors of waste generation. However, research has primarily focused on new build and has neglected refurbishment projects which become relevant due to an aging building stock in Sweden and Europe. Various actors are involved in refurbishment projects which makes it important to study each actor as well as tensions between them. By using a service ecosystem perspective and relying on 38 interviews, this paper aims to investigate tensions and barriers between actors within the service ecosystem of CDW for refurbishment projects in Sweden. Based on the results, spatial barriers are the most mentioned barrier which also create the highest number of tensions between project and contractor mother firm, subcontractors, waste recycling firms and society/citizens. The majority of the tensions are found between projects and the contractor mother firms, followed by tensions between projects and clients and projects and subcontractors. Unlike previous studies investigating only one of the actors waste management practices, this paper contributes by investigating the interactions between seven different actors which is important for improving waste management practices in refurbishment projects., Funding Agencies|Mistra Closing the Loop, the Foundation for Strategic Environmental Research [160026]

Artificial intelligence (AI) has been widely used in robotics, automation, finance, healthcare, etc. However, using AI for decision-making in sustainable product lifecycle operations is still challenging. One major challenge relates to the scarcity and uncertainties of data across the product lifecycle. This paper aims to develop a method that can adopt the most suitable AI techniques to support decision-making for sustainable operations based on the available lifecycle data. It identifies the key lifecycle stages in which AI, especially reinforcement learning (RL), can support decision-making. Then, a generalised procedure of using RL for decision support is proposed based on available lifecycle data, such as operation and maintenance data. The method has been validated in a case study of an international vehicle manufacturer, combined with modelling and simulation. The case study demonstrates the effectiveness of the method and identifies that RL is the current most appropriate method for maintenance scheduling based on limited available lifecycle data. This paper contributes to knowledge by demonstrating an empirically grounded industrial case using RL to optimise decision-making for improved product lifecycle sustainability by effectively prolonging the product lifetime and reducing environmental impact., Funding Agencies|VinnovaVinnova [2017-01649]

Waste management in the Architecture, Engineering and Construction (AEC) industry has been a major research topic owing to the AEC industry being one of the top contributors of waste generation. However, research has primarily focused on new build and has neglected refurbishment projects which become relevant due to an aging building stock in Sweden and Europe. Various actors are involved in refurbishment projects which makes it important to study each actor as well as tensions between them. By using a service ecosystem perspective and relying on 38 interviews, this paper aims to investigate tensions and barriers between actors within the service ecosystem of CDW for refurbishment projects in Sweden. Based on the results, spatial barriers are the most mentioned barrier which also create the highest number of tensions between project and contractor mother firm, subcontractors, waste recycling firms and society/citizens. The majority of the tensions are found between projects and the contractor mother firms, followed by tensions between projects and clients and projects and subcontractors. Unlike previous studies investigating only one of the actors waste management practices, this paper contributes by investigating the interactions between seven different actors which is important for improving waste management practices in refurbishment projects., Funding Agencies|Mistra Closing the Loop, the Foundation for Strategic Environmental Research [160026]

Artificial intelligence (AI) has been widely used in robotics, automation, finance, healthcare, etc. However, using AI for decision-making in sustainable product lifecycle operations is still challenging. One major challenge relates to the scarcity and uncertainties of data across the product lifecycle. This paper aims to develop a method that can adopt the most suitable AI techniques to support decision-making for sustainable operations based on the available lifecycle data. It identifies the key lifecycle stages in which AI, especially reinforcement learning (RL), can support decision-making. Then, a generalised procedure of using RL for decision support is proposed based on available lifecycle data, such as operation and maintenance data. The method has been validated in a case study of an international vehicle manufacturer, combined with modelling and simulation. The case study demonstrates the effectiveness of the method and identifies that RL is the current most appropriate method for maintenance scheduling based on limited available lifecycle data. This paper contributes to knowledge by demonstrating an empirically grounded industrial case using RL to optimise decision-making for improved product lifecycle sustainability by effectively prolonging the product lifetime and reducing environmental impact., Funding Agencies|VinnovaVinnova [2017-01649]

Waste management in the Architecture, Engineering and Construction (AEC) industry has been a major research topic owing to the AEC industry being one of the top contributors of waste generation. However, research has primarily focused on new build and has neglected refurbishment projects which become relevant due to an aging building stock in Sweden and Europe. Various actors are involved in refurbishment projects which makes it important to study each actor as well as tensions between them. By using a service ecosystem perspective and relying on 38 interviews, this paper aims to investigate tensions and barriers between actors within the service ecosystem of CDW for refurbishment projects in Sweden. Based on the results, spatial barriers are the most mentioned barrier which also create the highest number of tensions between project and contractor mother firm, subcontractors, waste recycling firms and society/citizens. The majority of the tensions are found between projects and the contractor mother firms, followed by tensions between projects and clients and projects and subcontractors. Unlike previous studies investigating only one of the actors waste management practices, this paper contributes by investigating the interactions between seven different actors which is important for improving waste management practices in refurbishment projects., Funding Agencies|Mistra Closing the Loop, the Foundation for Strategic Environmental Research [160026]

Purpose This article focuses on the risk that work disability policies lock people into work disability rather than promote durable health and return to work. We outline the concept of a work disability trap as a heuristic device to explore this policy paradox inherent in the design of most social insurance systems. Materials and methods This is a conceptual paper drawing on examples from existing research. Results We identify three manifestations of the disability trap: not overcoming disability; underperforming; and returning to work prematurely. The causes of these manifestations are identified as structural rather than based on malingering clients, while negative consequences are identified both on client and system levels. Conclusion We emphasize the need for systems built on trust and reasonable expectations, and the need for providing rehabilitation support independently of economic compensation. Universal basic income is introduced as a potential tool to ameliorate some of the consequences of the disability trap.

Time-dependent Origin-Destination (OD) matrices are an essential input to transportation models. A cost-efficient and widely used approach for estimating OD matrices involves the exploitation of flow counts from stationary traffic detectors. This estimation approach is also referred to as assignment-based OD matrix estimation because, typically, Dynamic Traffic Assignment (DTA) models are used to map the OD matrix to the link flows. The conventional DTA establish a complex non-linear relationship between the demand, and the link flows, adding an inherent complexity to the OD matrix estimation problem. In this paper, attempting to exploit the growing availability of Floating-Car Data (FCD), we suggest a solution approach that is based on a Data-Driven Network Assignment (DDNA) mechanism. The DDNA utilises the FCD from probe vehicles to capture congestion effects, providing a linear mapping of the OD matrix to the link flow observations. We present the results of two synthetic-data experiments that serve as proof of concept, indicating that if FCD are available, the computationally costly DTA may not be necessary for solving the OD matrix estimation problem., Funding Agencies|Swedish Transport Administration [TRV2018/132473, TRV2021/22404]; Swedish Energy Agency [46963-1]

The exact distribution of a classification function is often complicated to allow for easy numerical calculations of misclassification errors. The use of expansions is one way of dealing with this difficulty. In this paper, approximate probabilities of misclassification of the maximum likelihood-based discriminant function are established via an Edgeworth-type expansion based on the standard normal distribution for discriminating between two multivariate normal populations.

In this paper we address the problem of inconsistency in preference relations, pointing out the relevance of a meaningful representation in order to help decision maker to capture such inconsistencies. Dimension theory framework, despite its computational complexity, is considered here, pursuing in principle a decomposition of arbitrary preference relations in terms of linear orderings of alternatives. But we shall then stress that consistency should not be necessarily associated to a linear ordering. In this way, alternative decompositions of a preference relation can be proposed to decision maker, allowing an effective search for a useful representations of alternatives in terms of possible criteria. Such decompositions of our preference relations will then become the basis of a future decision aid model, always with the restricted aim of allowing the decision maker a better understanding of the problem. Inconsistencies may be not simply suppressed but understood, since they may contain relevant information., Depto. de Estadística e Investigación Operativa, Fac. de Ciencias Matemáticas, TRUE, pub

Risky alcohol use is a major public health problem globally and in Sri Lanka. While a reduction in alcohol consumption can result in physical, mental, and social benefits, behaviour change is difficult to achieve. Effective, context-adapted interventions are required to minimise alcohol-related harm at a community level. THEATRE is a complex, community-based intervention evaluating whether a promising Sri Lankan pilot study that utilised arts-based research to moderate alcohol use can be scaled up. While the scaled-up pilot study protocol is presented elsewhere, the aim of this protocol paper is to describe the intervention programme theory and evaluation design, and modifications made to the study resulting from COVID-19 and the financial crisis. Drawing on the Behaviour Change Wheel (BCW) and Theoretical Domains Framework, behaviour change theories are presented with potential pathways to guide implementation and evaluation. Alcohol consumption patterns and context of drinking is detailed. The multifaceted intervention targets individuals and communities using arts-based interventions. Four of nine BCW functions are employed in the design of the intervention: education, persuasion, modelling and enablement, and training. Modifications made to the study due to COVID-19 and the financial crisis are described. Ethical approval was obtained from the Ethics Review Committee, Faculty of Medicine and Allied Sciences, Rajarata University of Sri Lanka (ERC/2018/21-July 2018 and Feb 2022) and the University of Sydney (2019/006). Findings will be disseminated locally to community members and key stakeholders and via international peer-reviewed publications.

This paper focuses on how the chain of command is construed in Swedish municipal adult education. With a qualitative research approach and by drawing on the theoretical and methodological framework ‘What’s the “problem” represented to be?’ (WPR) approach, the aim is directed at identifying, interrogating, and reconstructing problem representations. The empirical material consists of contemporary key adult education policy that focuses on the chain of command and was analyzed in NVivo. Ethical considerations as well as data credibility, validity and reliability reflections were made in the form of WPR-guided self-reflexivity. The results indicate that both heads of education and principals are held responsible for the ‘weaknesses’ of the chain of command. Different solutions are also construed to solve the ‘problem’ that calls for increased trust between the actors in the chain of command. However, this trust seems to be underpinned by a request for more follow-ups, rather than a trust in the principal’s pedagogical leadership. The way that these issues are construed as specific kinds of ‘problems’ and ‘solutions’ has effects on the individuals that are involved in adult education. Based on the analysis, the need for policymakers to work on understanding the unintentional consequences of policies is stressed.

The exact distribution of a classification function is often complicated to allow for easy numerical calculations of misclassification errors. The use of expansions is one way of dealing with this difficulty. In this paper, approximate probabilities of misclassification of the maximum likelihood-based discriminant function are established via an Edgeworth-type expansion based on the standard normal distribution for discriminating between two multivariate normal populations.

The exact distribution of a classification function is often complicated to allow for easy numerical calculations of misclassification errors. The use of expansions is one way of dealing with this difficulty. In this paper, approximate probabilities of misclassification of the maximum likelihood-based discriminant function are established via an Edgeworth-type expansion based on the standard normal distribution for discriminating between two multivariate normal populations.

In this paper, we discuss the ethical responsibilities of being a role model as an engineering teacher in higher education. We draw on virtue ethics, care ethics, ethics of freedom and role modeling theory, using Grande's framework for engineering education. We argue that the three ethical theories give different views on the ethics of role modeling as a teacher. Virtue ethics implies that the teacher should behave as virtuously as possible to encourage students to emulate character traits. Care ethics implies that the ethics of role modeling is fundamentally about care practices, emphazising relationships and values such as attentiveness and responsibility. Ethics of freedom urges the teacher to grant individuals opportunities to develop and be free from the control of others. By using role modeling and ethical theory, we aim to show how theory has an impact on both teaching practices and could underpin empirical research in engineering education.

PURPOSE: Sepsis is a major global health problem with an estimated 49 million cases globally each year causing as many as 11 million deaths. The primary objective of this commentary is to describe the impacts of sepsis and critical illness on communication and swallowing function, and to discuss management strategies considering the Sustainable Development Goals (SDGs). RESULT: Communication and swallowing disabilities can occur with sepsis and critical illness. A holistic framework to optimise function, recovery, and future research priorities across the lifespan can be developed through the SDGs. CONCLUSION: Communication and swallowing disabilities following critical illness associated with sepsis have global impacts. Early multidisciplinary engagement is key to optimising individuals' function. Collaborative research, education, and public awareness is urgently needed to increase equity in health outcomes across populations. This commentary paper supports progress towards good health and well-being (SDG 3), quality education (SDG 4) and reduced inequalities (SDG 10).

Time-dependent Origin-Destination (OD) matrices are an essential input to transportation models. A cost-efficient and widely used approach for estimating OD matrices involves the exploitation of flow counts from stationary traffic detectors. This estimation approach is also referred to as assignment-based OD matrix estimation because, typically, Dynamic Traffic Assignment (DTA) models are used to map the OD matrix to the link flows. The conventional DTA establish a complex non-linear relationship between the demand, and the link flows, adding an inherent complexity to the OD matrix estimation problem. In this paper, attempting to exploit the growing availability of Floating-Car Data (FCD), we suggest a solution approach that is based on a Data-Driven Network Assignment (DDNA) mechanism. The DDNA utilises the FCD from probe vehicles to capture congestion effects, providing a linear mapping of the OD matrix to the link flow observations. We present the results of two synthetic-data experiments that serve as proof of concept, indicating that if FCD are available, the computationally costly DTA may not be necessary for solving the OD matrix estimation problem., Funding Agencies|Swedish Transport Administration [TRV2018/132473, TRV2021/22404]; Swedish Energy Agency [46963-1]

Purpose This article focuses on the risk that work disability policies lock people into work disability rather than promote durable health and return to work. We outline the concept of a work disability trap as a heuristic device to explore this policy paradox inherent in the design of most social insurance systems. Materials and methods This is a conceptual paper drawing on examples from existing research. Results We identify three manifestations of the disability trap: not overcoming disability; underperforming; and returning to work prematurely. The causes of these manifestations are identified as structural rather than based on malingering clients, while negative consequences are identified both on client and system levels. Conclusion We emphasize the need for systems built on trust and reasonable expectations, and the need for providing rehabilitation support independently of economic compensation. Universal basic income is introduced as a potential tool to ameliorate some of the consequences of the disability trap.

Time-dependent Origin-Destination (OD) matrices are an essential input to transportation models. A cost-efficient and widely used approach for estimating OD matrices involves the exploitation of flow counts from stationary traffic detectors. This estimation approach is also referred to as assignment-based OD matrix estimation because, typically, Dynamic Traffic Assignment (DTA) models are used to map the OD matrix to the link flows. The conventional DTA establish a complex non-linear relationship between the demand, and the link flows, adding an inherent complexity to the OD matrix estimation problem. In this paper, attempting to exploit the growing availability of Floating-Car Data (FCD), we suggest a solution approach that is based on a Data-Driven Network Assignment (DDNA) mechanism. The DDNA utilises the FCD from probe vehicles to capture congestion effects, providing a linear mapping of the OD matrix to the link flow observations. We present the results of two synthetic-data experiments that serve as proof of concept, indicating that if FCD are available, the computationally costly DTA may not be necessary for solving the OD matrix estimation problem., Funding Agencies|Swedish Transport Administration [TRV2018/132473, TRV2021/22404]; Swedish Energy Agency [46963-1]

Purpose This article focuses on the risk that work disability policies lock people into work disability rather than promote durable health and return to work. We outline the concept of a work disability trap as a heuristic device to explore this policy paradox inherent in the design of most social insurance systems. Materials and methods This is a conceptual paper drawing on examples from existing research. Results We identify three manifestations of the disability trap: not overcoming disability; underperforming; and returning to work prematurely. The causes of these manifestations are identified as structural rather than based on malingering clients, while negative consequences are identified both on client and system levels. Conclusion We emphasize the need for systems built on trust and reasonable expectations, and the need for providing rehabilitation support independently of economic compensation. Universal basic income is introduced as a potential tool to ameliorate some of the consequences of the disability trap.

This paper focuses on how the chain of command is construed in Swedish municipal adult education. With a qualitative research approach and by drawing on the theoretical and methodological framework ‘What’s the “problem” represented to be?’ (WPR) approach, the aim is directed at identifying, interrogating, and reconstructing problem representations. The empirical material consists of contemporary key adult education policy that focuses on the chain of command and was analyzed in NVivo. Ethical considerations as well as data credibility, validity and reliability reflections were made in the form of WPR-guided self-reflexivity. The results indicate that both heads of education and principals are held responsible for the ‘weaknesses’ of the chain of command. Different solutions are also construed to solve the ‘problem’ that calls for increased trust between the actors in the chain of command. However, this trust seems to be underpinned by a request for more follow-ups, rather than a trust in the principal’s pedagogical leadership. The way that these issues are construed as specific kinds of ‘problems’ and ‘solutions’ has effects on the individuals that are involved in adult education. Based on the analysis, the need for policymakers to work on understanding the unintentional consequences of policies is stressed.

ChatGPT, a sophisticated online chatbot, sent shockwaves through many sectors once reports filtered through that it could pass exams. In higher education, it has raised many questions about the authenticity of assessment and challenges in detecting plagiarism. Amongst the resulting frenetic hubbub, hints of potential opportunities in how ChatGPT could support learning and the development of critical thinking have also emerged. In this paper, we examine how ChatGPT may affect assessment in engineering education by exploring ChatGPT responses to existing assessment prompts from ten subjects across seven Australian universities. We explore the strengths and weaknesses of current assessment practice and discuss opportunities on how ChatGPT can be used to facilitate learning. As artificial intelligence is rapidly improving, this analysis sets a benchmark for ChatGPT’s performance as of early 2023 in responding to engineering education assessment prompts. ChatGPT did pass some subjects and excelled with some assessment types. Findings suggest that changes in current practice are needed, as typically with little modification to the input prompts, ChatGPT could generate passable responses to many of the assessments, and it is only going to get better as future versions are trained on larger data sets.

The literature on laboratory objectives in engineering education research is scattered and inconsistent. Systematic literature reviews identified the need for better understanding. This paper ranks the laboratory learning objectives across the cognitive, psychomotor and affective domains to improve scaffolding. It provides an opportunity for reflection, a pathway to confirm assessment alignment, and opens future research areas. To accomplish this, the Laboratory Learning Objectives Measurement (LLOM) instrument is used to survey 160 academics from around the world representing 18 engineering disciplines. The results suggest that the collective ranking order does represent a framework that can be used broadly. However, for greater alignment with consensus thinking, discipline rankings should be used. The cognitive domain was deemed the most important. These results provide the community’s opinion and may not necessarily be best practice, providing an opportunity for reflection.

The term ‘impact’ is everywhere. Organizations and individuals want to fund projects for impact, measure impact, and showcase the impact of effort, expertise and financial investment, but clear definitions and understandings of what having an impact really means for people and institutions appear lacking or ad-hoc. This paper explores ‘impact’ in the areas of education and research into government practice. For governments, the impact agenda involves operating in increasingly tight fiscal environments with mounting pressure to articulate and demonstrate return on investment. For education providers, there are increasing calls to justify and prove why investment in education is an efficient and effective endeavor. For universities, this includes a shift from a traditional publication-focused research impact culture to a wider societal impact one that demonstrates direct and indirect benefits to society. This paper conceptualizes impact as a “puzzle” with many pieces, with education and research making up key pieces that can and need to fit together better. In doing so, the paper identifies four problem areas to help guide thinking toward clarity about what ‘impact’ entails. To aid collective progress in this space, we detail key issues facing the education and research sectors. Based on our analysis we arrive at a set of questions intended to help guide thinking and actions toward collectively increasing the ability to generate and demonstrate the impact of both into government practice and society at large.

PURPOSE: This review articulates current understanding of the aesthetic, artistic and creative contributions that Dance makes to Health and Wellbeing across the lifecourse within publications 2000-2019, an under-researched area. METHODS: Review Questions: What are the aesthetic, artistic and creative contributions that Dance makes to Health and Wellbeing across the lifecourse? And what methodologies are appropriate for investigating these contributions? A database keyword search identified 769 articles and 91 evaluations. 109 documents were identified for further in-depth analysis and rating, resulting in 24 papers (11 articles, 3 PhD studies, 10 evaluation reports), which were thematically analysed. RESULTS: Findings offer seven interrelated contributions that Dance makes to Health and Wellbeing: embodiment, identity, belonging, self-worth, aesthetics, affective responses and creativity. There was less insight regarding different methodologies, and discussions focused on quantitative data's limitations. There were insights into inclusion of embodied voices, subjective accounts, and lived experiences. CONCLUSION: Whilst acknowledging challenges, this paper illuminates the key contributions of dance to arts and health. It provides a future conceptual research agenda (prioritizing identity and creativity) and associated methodological developments. It recommends expanding geographical/lifecourse research, better defining terms, fuller epistemological critiques to open space for new methodologies, and continued attendance to appropriate rigour criteria.