The State-of-the-Art Survey on Optimization Methods for Cyber-physical Networks

Cyber-Physical Systems (CPS) are increasingly complex and frequently integrated into modern societies via critical infrastructure systems, products, and services. Consequently, there is a need for reliable functionality of these complex systems under various scenarios, from physical failures due to aging, through to cyber attacks. Indeed, the development of effective strategies to restore disrupted infrastructure systems continues to be a major challenge. Hitherto, there have been an increasing number of papers evaluating cyber-physical infrastructures, yet a comprehensive review focusing on mathematical modeling and different optimization methods is still lacking. Thus, this review paper appraises the literature on optimization techniques for CPS facing disruption, to synthesize key findings on the current methods in this domain. A total of 108 relevant research papers are reviewed following an extensive assessment of all major scientific databases. The main mathematical modeling practices and optimization methods are identified for both deterministic and stochastic formulations, categorizing them based on the solution approach (exact, heuristic, meta-heuristic), objective function, and network size. We also perform keyword clustering and bibliographic coupling analyses to summarize the current research trends. Future research needs in terms of the scalability of optimization algorithms are discussed. Overall, there is a need to shift towards more scalable optimization solution algorithms, empowered by data-driven methods and machine learning, to provide reliable decision-support systems for decision-makers and practitioners

Multiple Object Tracking in Urban Traffic Scenes with a Multiclass Object Detector

Multiple object tracking (MOT) in urban traffic aims to produce the trajectories of the different road users that move across the field of view with different directions and speeds and that can have varying appearances and sizes. Occlusions and interactions among the different objects are expected and common due to the nature of urban road traffic. In this work, a tracking framework employing classification label information from a deep learning detection approach is used for associating the different objects, in addition to object position and appearances. We want to investigate the performance of a modern multiclass object detector for the MOT task in traffic scenes. Results show that the object labels improve tracking performance, but that the output of object detectors are not always reliable.Comment: 13th International Symposium on Visual Computing (ISVC

Multi-task localization of the hemidiaphragms and lung segmentation in portable chest X-ray images of COVID-19 patients

BACKGROUND: The COVID-19 can cause long-term symptoms in the patients after they overcome the disease. Given that this disease mainly damages the respiratory system, these symptoms are often related with breathing problems that can be caused by an affected diaphragm. The diaphragmatic function can be assessed with imaging modalities like computerized tomography or chest X-ray. However, this process must be performed by expert clinicians with manual visual inspection. Moreover, during the pandemic, the clinicians were asked to prioritize the use of portable devices, preventing the risk of cross-contamination. Nevertheless, the captures of these devices are of a lower quality. OBJECTIVES: The automatic quantification of the diaphragmatic function can determine the damage of COVID-19 on each patient and assess their evolution during the recovery period, a task that could also be complemented with the lung segmentation. METHODS: We propose a novel multi-task fully automatic methodology to simultaneously localize the position of the hemidiaphragms and to segment the lung boundaries with a convolutional architecture using portable chest X-ray images of COVID-19 patients. For that aim, the hemidiaphragms’ landmarks are located adapting the paradigm of heatmap regression. RESULTS: The methodology is exhaustively validated with four analyses, achieving an 82.31% 2.78% of accuracy when localizing the hemidiaphragms’ landmarks and a Dice score of 0.9688 0.0012 in lung segmentation. CONCLUSIONS: The results demonstrate that the model is able to perform both tasks simultaneously, being a helpful tool for clinicians despite the lower quality of the portable chest X-ray images

Dynamic characterisation of Össur Flex-Run prosthetic feet for a more informed prescription

Background: The current method of prescribing composite Energy Storing and 6 Returning (ESR) feet is subjective and is based only on the amputee’s static body 7 weight/mass. 8 Objectives: The aim is to investigate their unique design features through identifying 9 and analysing their dynamic characteristics, utilising modal analysis, to determine 10 their mode shapes, natural damping and natural frequencies. Full understanding of 11 the dynamic characteristics can inform on how to tune a foot to match an amputee’s 12 gait and body condition. 13 Methods: This paper presents the modal analysis results of the full range of Össur 14 Flex-Run running feet that are commercially available (1LO-9LO). 15 Results: It is shown that both the undamped natural frequency and stiffness increase 16 linearly from the lowest to highest stiffness category of foot. The effect of over-load 17 and under-loading on natural frequencies is also presented. The damping factor for 18 each foot has been experimentally determined and it was found to be ranging 19 between 1.5-2.0%. An analysis of the mode shapes also showed a unique design 20 feature of these feet that is hypothesised to enhance their performance. 21 Conclusions: A better understanding of the feet dynamic characteristics can help to 22 tune the feet to the user’s requirements. 23 (194 words

Eliciting preferences for continuing medication among adult patients and parents of children with attention‐deficit hyperactivity disorder

Background: Adherence to medication for attention‐deficit hyperactivity disorder (ADHD) is less than optimal. Previous studies have primarily focused on qualitative assessment of factors that influence medication adherence. Objective: This study aimed to quantify the factors that influence patient and parent preferences for continuing ADHD medication. Method: A discrete‐choice experiment was conducted to investigate preferences. Adults, and parents of children, with ADHD were presented with eight hypothetical choice tasks of three options (Medication A, Medication B, No Medication) described by six attributes related to medication outcomes. Preferences were estimated using a mixed multinomial logit model. Results: Overall, respondents' preferences (n = 216) for continuing medication were negative (mean [β] = −1.426, p < .001); however, a significant heterogeneity in preferences was observed amongst respondents (standard deviation = 0.805, p < .001). Improvements in education, aggressive behaviour, social behaviour and family functioning, and side effects and stigma, influenced respondents' decision to continue taking medication. The respondents were willing to continue medication if they experienced positive effects, but side effects (even moderate) were the strongest concern for not continuing medication. While side effects were the most important factor for both adult patients and parents of children with ADHD, improvement in education was relatively more important for adults and improvement in aggressive behaviour, social behaviour and family functioning was relatively more important for parents of children with ADHD. Parents were more likely to not continue a medication with severe side effects even at the highest level of improvement in education. Conclusions: Side effects are the most important factor that influenced preferences for continuing medication for both adults with ADHD, as well as parents of children with ADHD. While overall the respondents preferred not to take/give medication, discrete‐choice experiment showed that the relative importance of factors that influenced continuation of medications was different for the two groups. Patient and Public Involvement: Adults, and parents of children, with ADHD participated in this study by completing the online questionnaire. The questionnaire was based on findings of research in the literature, as well as earlier focus groups conducted with adults, and parents of children, with ADHD. The face validity of the questionnaire was determined by asking parents of children, and adults, with ADHD (n = 3) to complete the survey and participate in a short discussion on their understanding of the questions and their recommendations on improving the clarity of the survey

Atherosclerosis and autoimmunity: a growing relationship

Atherosclerosis is regarded as one of the leading causes of mortality and morbidity in the world. Nowadays, it seems that atherosclerosis cannot be defined merely through the Framingham traditional risk factors and that autoimmunity settings exert a remarkable role in its mechanobiology. Individuals with autoimmune disorders show enhanced occurrence of cardiovascular complications and subclinical atherosclerosis. The mechanisms underlying the atherosclerosis in disorders like rheumatoid arthritis, systemic lupus erythematosus, antiphospholipid syndrome, systemic sclerosis and Sjögren's syndrome, seem to be the classical risk factors. However, chronic inflammatory processes and abnormal immune function may also be involved in atherosclerosis development. Autoantigens, autoantibodies, infectious agents and pro-inflammatory mediators exert a role in that process. Being armed with the mechanisms underlying autoimmunity in the etiopathogenesis of atherosclerosis in rheumatic autoimmune disorders and the shared etiologic pathway may result in substantial developing therapeutics for these patients. © 2018 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Lt

Atherosclerosis and autoimmunity: a growing relationship

Atherosclerosis is regarded as one of the leading causes of mortality and morbidity in the world. Nowadays, it seems that atherosclerosis cannot be defined merely through the Framingham traditional risk factors and that autoimmunity settings exert a remarkable role in its mechanobiology. Individuals with autoimmune disorders show enhanced occurrence of cardiovascular complications and subclinical atherosclerosis. The mechanisms underlying the atherosclerosis in disorders like rheumatoid arthritis, systemic lupus erythematosus, antiphospholipid syndrome, systemic sclerosis and Sjögren's syndrome, seem to be the classical risk factors. However, chronic inflammatory processes and abnormal immune function may also be involved in atherosclerosis development. Autoantigens, autoantibodies, infectious agents and pro-inflammatory mediators exert a role in that process. Being armed with the mechanisms underlying autoimmunity in the etiopathogenesis of atherosclerosis in rheumatic autoimmune disorders and the shared etiologic pathway may result in substantial developing therapeutics for these patients. © 2018 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Lt

Delineating COVID-19 subgroups using routine clinical data identifies distinct in-hospital outcomes

The COVID-19 pandemic has been a great challenge to healthcare systems worldwide. It highlighted the need for robust predictive models which can be readily deployed to uncover heterogeneities in disease course, aid decision-making and prioritise treatment. We adapted an unsupervised data-driven model-SuStaIn, to be utilised for short-term infectious disease like COVID-19, based on 11 commonly recorded clinical measures. We used 1344 patients from the National COVID-19 Chest Imaging Database (NCCID), hospitalised for RT-PCR confirmed COVID-19 disease, splitting them equally into a training and an independent validation cohort. We discovered three COVID-19 subtypes (General Haemodynamic, Renal and Immunological) and introduced disease severity stages, both of which were predictive of distinct risks of in-hospital mortality or escalation of treatment, when analysed using Cox Proportional Hazards models. A low-risk Normal-appearing subtype was also discovered. The model and our full pipeline are available online and can be adapted for future outbreaks of COVID-19 or other infectious disease

Codesigning a Community Health Navigator program to assist patients to transition from hospital to community

Background This study aimed to identify the potential roles for Community Health Navigators (CHNs) in addressing problems faced by patients on discharge from hospital to the community, and attitudes and factors which may influence their adoption.Methods Twenty-six qualitative interviews and an online codesign workshop were conducted with patients, nurses, general practice staff, health service managers, community health workers, general practitioners, medical specialists, and pharmacists in the Sydney Local Health District. Qualitative themes from the interviews and workshop transcripts were analysed inductively and subsequently grouped according to a socio-ecological model.Results CHNs could assist patients to navigate non-clinical problems experienced by patients on discharge through assessing needs, establishing trust, providing social and emotional support that is culturally and linguistically appropriate, engaging family and carers, supporting medication adherence, and helping to arrange and attend follow up health and other appointments. Important factors for the success of the CHNs in the performance and sustainability of their roles were the need to establish effective communication and trust with other healthcare team members, be accepted by patients, have access to information about referral and support services, receive formal recognition of their training and experience, and be supported by appropriate supervision.Conclusions This study was unique in exploring the potential role of CHNs in addressing problems faced by patients on discharge from Australian hospitals and the factors influencing their adoption. It informed training and supervision needs and further research to evaluate CHNs’ effectiveness and the acceptance of their role within the healthcare team