Evolutionary Digital Twin-Oriented Complex Networked Systems driven by node features and the mutation of feature preferences.

Accurate modelling of complex social systems, where people interact with each other and those interactions change over time, has been a research challenge for many years. This study proposes an evolutionary Digital Twin-Oriented Complex Networked System (DT-CNS) framework that considers heterogeneous node features and changeable connection preferences. We create heterogeneous preference mutation mechanisms to characterise nodes' adaptive decisions on preference mutation in response to interaction patterns and epidemic risks. In this space, we use nodes' interaction utilities to characterise the positive feedback from interactions and negative impact of epidemic risks. We also introduce social capital constraint to harness the density of social connections better. The nodes' heterogeneous preference mutation styles include the (i)inactive style that keeps initial social preferences, (ii) ignorant style that randomly mutates preferences, (iii) egocentric style that optimises individual interaction utility, (iv) cooperative style that optimises the total interaction utilities by group decisions and (v) collaborative style that further allows the cooperative nodes to transfer social capital. Our simulation experiments on evolutionary DT-CNSs reveal that heterogeneous preference mutation styles lead to various interaction and infection patterns. The results also show that (i) increasing social capital enables higher interactions but higher infection risks and uncertainty in decision-making; (ii) group decisions outperform individual decisions by eliminating the unawareness of the decisions of other nodes; (iii) the collaborative nodes under a strict social capital limit can promote interactions, reduce infection risks and achieve higher overall interaction utilities.

Examining the Role of Structural and Functional Social Network Characteristics in the Context of Chronic Pain: An Ego-centered Network Design.

The well-being and functioning of individuals with chronic pain (CP) vary significantly. Social factors, such as social integration, may help explain this differential impact. Specifically, structural (network size, density) as well as functional (perceived social support, conflict) social network characteristics may play a role. However, it is not yet clear whether and how these variables are associated with each other. Objectives were to examine 1) both social network characteristics in individuals with primary and secondary CP, 2) the association between structural network characteristics and mental distress and functioning/participation in daily life, and 3) whether the network's functionality mediated the association between structural network characteristics and mental distress, respectively, functioning/participation in daily life. Using an online ego-centered social network tool, cross-sectional data were collected from 303 individuals with CP (81.85% women). No significant differences between individuals with fibromyalgia versus secondary CP were found regarding network size and density. In contrast, ANCOVA models showed lower levels of perceived social support and higher levels of conflict in primary (vs secondary) CP. Structural equation models showed that 1) larger network size indirectly predicted lower mental distress via lower levels of conflict; 2) higher network density increased mental distress via the increase of conflict levels. Network size or density did not (in)directly predict functioning/participation in daily life. The findings highlight that the role of conflict, in addition to support, should not be underestimated as a mediator for mental well-being. Research on explanatory mechanisms for associations between the network's structure, functionality, and well-being is warranted. PERSPECTIVE: This paper presents results on associations between structural (network size, density) and functional (social support, conflict) social network characteristics and well-being in the context of CP by making use of an ego-centered network design. Results suggest an indirect association between structural network characteristics and individuals with CP their mental well-being.

Towards Digital Twin-Oriented Complex Networked Systems: Introducing heterogeneous node features and interaction rules.

This study proposes an extendable modelling framework for Digital Twin-Oriented Complex Networked Systems (DT-CNSs) with a goal of generating networks that faithfully represent real-world social networked systems. Modelling process focuses on (i) features of nodes and (ii) interaction rules for creating connections that are built based on individual node's preferences. We conduct experiments on simulation-based DT-CNSs that incorporate various features and rules about network growth and different transmissibilities related to an epidemic spread on these networks. We present a case study on disaster resilience of social networks given an epidemic outbreak by investigating the infection occurrence within specific time and social distance. The experimental results show how different levels of the structural and dynamics complexities, concerned with feature diversity and flexibility of interaction rules respectively, influence network growth and epidemic spread. The analysis revealed that, to achieve maximum disaster resilience, mitigation policies should be targeted at nodes with preferred features as they have higher infection risks and should be the focus of the epidemic control.

Inferring actual treatment pathways from patient records.

OBJECTIVE: Treatment pathways are step-by-step plans outlining the recommended medical care for specific diseases; they get revised when different treatments are found to improve patient outcomes. Examining health records is an important part of this revision process, but inferring patients' actual treatments from health data is challenging due to complex event-coding schemes and the absence of pathway-related annotations. The objective of this study is to develop a method for inferring actual treatment steps for a particular patient group from administrative health records - a common form of tabular healthcare data - and address several technique- and methodology-based gaps in treatment pathway-inference research. METHODS: We introduce Defrag, a method for examining health records to infer the real-world treatment steps for a particular patient group. Defrag learns the semantic and temporal meaning of healthcare event sequences, allowing it to reliably infer treatment steps from complex healthcare data. To our knowledge, Defrag is the first pathway-inference method to utilise a neural network (NN), an approach made possible by a novel, self-supervised learning objective. We also developed a testing and validation framework for pathway inference, which we use to characterise and evaluate Defrag's pathway inference ability, establish benchmarks, and compare against baselines. RESULTS: We demonstrate Defrag's effectiveness by identifying best-practice pathway fragments for breast cancer, lung cancer, and melanoma in public healthcare records. Additionally, we use synthetic data experiments to demonstrate the characteristics of the Defrag inference method, and to compare Defrag to several baselines, where it significantly outperforms non-NN-based methods. CONCLUSIONS: Defrag offers an innovative and effective approach for inferring treatment pathways from complex health data. Defrag significantly outperforms several existing pathway-inference methods, but computationally-derived treatment pathways are still difficult to compare against clinical guidelines. Furthermore, the open-source code for Defrag and the testing framework are provided to encourage further research in this area.

Machine learning for administrative health records: A systematic review of techniques and applications.

Machine learning provides many powerful and effective techniques for analysing heterogeneous electronic health records (EHR). Administrative Health Records (AHR) are a subset of EHR collected for administrative purposes, and the use of machine learning on AHRs is a growing subfield of EHR analytics. Existing reviews of EHR analytics emphasise that the data-modality of the EHR limits the breadth of suitable machine learning techniques, and pursuable healthcare applications. Despite emphasising the importance of data modality, the literature fails to analyse which techniques and applications are relevant to AHRs. AHRs contain uniquely well-structured, categorically encoded records which are distinct from other data-modalities captured by EHRs, and they can provide valuable information pertaining to how patients interact with the healthcare system. This paper systematically reviews AHR-based research, analysing 70 relevant studies and spanning multiple databases. We identify and analyse which machine learning techniques are applied to AHRs and which health informatics applications are pursued in AHR-based research. We also analyse how these techniques are applied in pursuit of each application, and identify the limitations of these approaches. We find that while AHR-based studies are disconnected from each other, the use of AHRs in health informatics research is substantial and accelerating. Our synthesis of these studies highlights the utility of AHRs for pursuing increasingly complex and diverse research objectives despite a number of pervading data- and technique-based limitations. Finally, through our findings, we propose a set of future research directions that can enhance the utility of AHR data and machine learning techniques for health informatics research.

New Materials Based on Molecular Interaction between Hyaluronic Acid and Bovine Albumin.

In this work, the interactions between hyaluronic acid and bovine serum albumin were investigated. The film-forming properties of the mixture were proven, and the mechanical and surface properties of the films were measured. The results showed the interactions between hyaluronic acid and albumin, mainly by hydrogen bonds. Molecular docking was used for the visualization of the interactions. The films obtained from the mixture of hyaluronic acid possessed different properties to films obtained from the single component. The addition of bovine serum albumin to hyaluronic acid led to a decrease in the mechanical properties, and to an increase in the surface roughness of the film. The new materials that have been obtained by blending can form a new group of materials for biomedicine and cosmetology.

Encoding edge type information in graphlets.

Graph embedding approaches have been attracting increasing attention in recent years mainly due to their universal applicability. They convert network data into a vector space in which the graph structural information and properties are maximumly preserved. Most existing approaches, however, ignore the rich information about interactions between nodes, i.e., edge attribute or edge type. Moreover, the learned embeddings suffer from a lack of explainability, and cannot be used to study the effects of typed structures in edge-attributed networks. In this paper, we introduce a framework to embed edge type information in graphlets and generate a Typed-Edge Graphlets Degree Vector (TyE-GDV). Additionally, we extend two combinatorial approaches, i.e., the colored graphlets and heterogeneous graphlets approaches to edge-attributed networks. Through applying the proposed method to a case study of chronic pain patients, we find that not only the network structure of a patient could indicate his/her perceived pain grade, but also certain social ties, such as those with friends, colleagues, and healthcare professionals, are more crucial in understanding the impact of chronic pain. Further, we demonstrate that in a node classification task, the edge-type encoded graphlets approaches outperform the traditional graphlet degree vector approach by a significant margin, and that TyE-GDV could achieve a competitive performance of the combinatorial approaches while being far more efficient in space requirements.

Health Centres 75+ as a New Model to Improve Care for Older People in Poland.

According to a recent national audit, the cost of treating patients in geriatric wards is 20-30% less compared to those treated in internal medicine wards. Yet, geriatric care remains largely underdeveloped in Poland, with few human, material, and financial resources. Despite numerous attempts to raise the profile of geriatrics over the years, little progress has been achieved. In 2019, experts under the President of Poland proposed the creation of a network of Health Centres 75+ as the first pillar of geriatric care. These are meant to provide ambulatory services for older people and coordinate provision of other health and social care services at the county level. The goal is to create a community model of care, whereby older people would receive needed services close to their place of residence, allowing them to live independently for as long as possible. Although the proposal has been welcomed by the geriatric community and the patients, the acute shortages of human, physical, and financial resources raise concerns about its feasibility. However, the new strategic plans for the health system propose solutions that appear to be supportive of the new proposal, and the Office of the President is discussing joining forces with the Ministry of Health to improve its chances of implementation. Given the increasing pace of population ageing and underdeveloped provision of geriatric services, these efforts are very much needed.

A reform proposal from 2019 aims to improve coordination of health services in Poland by strengthening the role of the counties.

Numerous attempts have been undertaken over the past two decades to improve the coordination of health services in Poland. These have usually focused on specific groups of patients or conditions, usually encompassing various types of specialist care, with only a few initiatives including a wider range of health services or sectors. These efforts have not been helped by the fragmentation of responsibilities between the various levels of territorial self-government, which are the founding bodies for different types of public providers. In 2019, a new policy initiative of the Ministry of Health proposed the establishment of County Health Centres that would improve integration of primary health care with specialist outpatient care, inpatient care in the county hospitals (hospitals of the 1st reference level), and other services at the level of the county. This would constitute the so-called "core system of health security" and support reorientation of health services towards PHC and the community and away from specialist hospitals. With its focus on health promotion and disease prevention and tailoring provision to the needs of the local populations, the proposal resembles examples of population health models introduced in several other countries, and offers a chance to improve the allocation of resources and to reduce the persisting health disparities across the country.

Exploring variation of coverage and access to dental care for adults in 11 European countries: a vignette approach.

BACKGROUND: Oral health, coupled with rising awareness on the impact that limited dental care coverage has on oral health and general health and well-being, has received increased attention over the past few years. The purpose of the study was to compare the statutory coverage and access to dental care for adult services in 11 European countries using a vignette approach. METHODS: We used three patient vignettes to highlight the differences of the dimensions of coverage and access to dental care (coverage, cost-sharing and accessibility). The three vignettes describe typical care pathways for patients with the most common oral health conditions (caries, periodontal disease, edentulism). The vignettes were completed by health services researchers knowledgeable on dental care, dentists, or teams consisting of a health systems expert working together with dental specialists. RESULTS: Completed vignettes were received from 11 countries: Bulgaria, Estonia, France, Germany, Republic of Ireland (Ireland), Lithuania, the Netherlands, Poland, Portugal, Slovakia and Sweden. While emergency dental care, tooth extraction and restorative care for acute pain due to carious lesions are covered in most responding countries, root canal treatment, periodontal care and prosthetic restoration often require cost-sharing or are entirely excluded from the benefit basket. Regular dental visits are also limited to one visit per year in many countries. Beyond financial barriers due to out-of-pocket payments, patients may experience very different physical barriers to accessing dental care. The limited availability of contracted dentists (especially in rural areas) and the unequal distribution and lack of specialised dentists are major access barriers to public dental care. CONCLUSIONS: According to the results, statutory coverage of dental care varies across European countries, while access barriers are largely similar. Many dental services require substantial cost-sharing in most countries, leading to high out-of-pocket spending. Socioeconomic status is thus a main determinant for access to dental care, but other factors such as geography, age and comorbidities can also inhibit access and affect outcomes. Moreover, coverage in most oral health systems is targeted at treatment and less at preventative oral health care.

Effect of Chitosan Deacetylation on Its Affinity to Type III Collagen: A Molecular Dynamics Study.

The ability to form strong intermolecular interactions by linear glucosamine polysaccharides with collagen is strictly related to their nonlinear dynamic behavior and hence bio-lubricating features. Type III collagen plays a crucial role in tissue regeneration, and its presence in the articular cartilage affects its bio-technical features. In this study, the molecular dynamics methodology was applied to evaluate the effect of deacetylation degree on the chitosan affinity to type III collagen. The computational procedure employed docking and geometry optimizations of different chitosan structures characterized by randomly distributed deacetylated groups. The eight different degrees of deacetylation from 12.5% to 100% were taken into account. We found an increasing linear trend (R2 = 0.97) between deacetylation degree and the collagen-chitosan interaction energy. This can be explained by replacing weak hydrophobic contacts with more stable hydrogen bonds involving amino groups in N-deacetylated chitosan moieties. In this study, the properties of chitosan were compared with hyaluronic acid, which is a natural component of synovial fluid and cartilage. As we found, when the degree of deacetylation of chitosan was greater than 0.4, it exhibited a higher affinity for collagen than in the case of hyaluronic acid.

NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size.

Neural architecture search (NAS) has attracted a lot of attention and has been illustrated to bring tangible benefits in a large number of applications in the past few years. Architecture topology and architecture size have been regarded as two of the most important aspects for the performance of deep learning models and the community has spawned lots of searching algorithms for both of those aspects of the neural architectures. However, the performance gain from these searching algorithms is achieved under different search spaces and training setups. This makes the overall performance of the algorithms incomparable and the improvement from a sub-module of the searching model unclear. In this paper, we propose NATS-Bench, a unified benchmark on searching for both topology and size, for (almost) any up-to-date NAS algorithm. NATS-Bench includes the search space of 15,625 neural cell candidates for architecture topology and 32,768 for architecture size on three datasets. We analyze the validity of our benchmark in terms of various criteria and performance comparison of all candidates in the search space. We also show the versatility of NATS-Bench by benchmarking 13 recent state-of-the-art NAS algorithms on it. All logs and diagnostic information trained using the same setup for each candidate are provided. This facilitates a much larger community of researchers to focus on developing better NAS algorithms in a more comparable and computationally effective environment. All codes are publicly available at: https://xuanyidong.com/assets/projects/NATS-Bench.

Data-driven approach for tailoring facilitation strategies to overcome implementation barriers in community pharmacy.

BACKGROUND: Implementation research has delved into barriers to implementing change and interventions for the implementation of innovation in practice. There remains a gap, however, that fails to connect implementation barriers to the most effective implementation strategies and provide a more tailored approach during implementation. This study aimed to explore barriers for the implementation of professional services in community pharmacies and to predict the effectiveness of facilitation strategies to overcome implementation barriers using machine learning techniques. METHODS: Six change facilitators facilitated a 2-year change programme aimed at implementing professional services across community pharmacies in Australia. A mixed methods approach was used where barriers were identified by change facilitators during the implementation study. Change facilitators trialled and recorded tailored facilitation strategies delivered to overcome identified barriers. Barriers were coded according to implementation factors derived from the Consolidated Framework for Implementation Research and the Theoretical Domains Framework. Tailored facilitation strategies were coded into 16 facilitation categories. To predict the effectiveness of these strategies, data mining with random forest was used to provide the highest level of accuracy. A predictive resolution percentage was established for each implementation strategy in relation to the barriers that were resolved by that particular strategy. RESULTS: During the 2-year programme, 1131 barriers and facilitation strategies were recorded by change facilitators. The most frequently identified barriers were a 'lack of ability to plan for change', 'lack of internal supporters for the change', 'lack of knowledge and experience', 'lack of monitoring and feedback', 'lack of individual alignment with the change', 'undefined change objectives', 'lack of objective feedback' and 'lack of time'. The random forest algorithm used was able to provide 96.9% prediction accuracy. The strategy category with the highest predicted resolution rate across the most number of implementation barriers was 'to empower stakeholders to develop objectives and solve problems'. CONCLUSIONS: Results from this study have provided a better understanding of implementation barriers in community pharmacy and how data-driven approaches can be used to predict the effectiveness of facilitation strategies to overcome implementation barriers. Tailored facilitation strategies such as these can increase the rate of real-time implementation of innovations in healthcare, leading to an industry that can confidently and efficiently adapt to continuous change.

Directed closure coefficient and its patterns.

The triangle structure, being a fundamental and significant element, underlies many theories and techniques in studying complex networks. The formation of triangles is typically measured by the clustering coefficient, in which the focal node is the centre-node in an open triad. In contrast, the recently proposed closure coefficient measures triangle formation from an end-node perspective and has been proven to be a useful feature in network analysis. Here, we extend it by proposing the directed closure coefficient that measures the formation of directed triangles. By distinguishing the direction of the closing edge in building triangles, we further introduce the source closure coefficient and the target closure coefficient. Then, by categorising particular types of directed triangles (e.g., head-of-path), we propose four closure patterns. Through multiple experiments on 24 directed networks from six domains, we demonstrate that at network-level, the four closure patterns are distinctive features in classifying network types, while at node-level, adding the source and target closure coefficients leads to significant improvement in link prediction task in most types of directed networks.

Testing the 2017 PHC reform through pilots: Strengthening prevention and chronic care coordination.

Numerous official reports have highlighted insufficient provision of preventive services within primary health care (PHC) in Poland. Other identified weaknesses include inappropriate referrals to ambulatory care that contribute to long waiting times for specialist consultations. Since mid-2018, a new model of PHC organization has been piloted and can be seen as an attempt to address some of these weaknesses. It draws on the Primary Health Care Act of 2017 and puts much more emphasis on disease prevention and health promotion within PHC as well as shifts management of common chronic conditions to multidisciplinary PHC teams. The implementation of this model has been supported by a range of financial and non-financial measures, including a special grant that helps PHC practices to adapt their IT systems to the requirements of the pilot. Yet, the overall requirements were prohibitive to most PHC practices and only 42 were eventually included in the pilot. In this paper, we describe the content of this model, the difficulties in its implementation and how they were addressed and discuss its possible effects on PHC and the health system more broadly.

Collagen Based Materials in Cosmetic Applications: A Review.

This review provides a report on properties and recent advances in the application of collagen in cosmetics. Collagen is a structural protein found in animal organisms where it provides for the fundamental structural support. Most commonly it is extracted from mammalian and fish skin. Collagen has attracted significant academic interest as well as the attention of the cosmetic industry due to its interesting properties that include being a natural humectant and moisturizer for the skin. This review paper covers the biosynthesis of collagen, the sources of collagen used in the cosmetic industry, and the role played by this protein in cosmetics. Future aspects regarding applications of collagen-based materials in cosmetics have also been mentioned.

Hyaluronic Acid as a Component of Natural Polymer Blends for Biomedical Applications: A Review.

In this review, we provide a report on recent studies in the field of research on the blends of hyaluronic acid with other natural polymers, namely collagen and chitosan. Hyaluronic acid has attracted significant interest in biomedical and cosmetic applications due to its interesting properties. In recent years, blends of hyaluronic acid with other polymers have been studied for new materials development. New materials may show improved properties that are important in the biomedical applications and in cosmetic preparations. In this review paper, the structure, preparation, and properties of hyaluronic acid blends with collagen and chitosan have been discussed and examples of new materials based on such blends have been presented. A comparison of the currently available information in the field has been shown. Future aspects in the field of hyaluronic acid blends and their applications in the biomedical and cosmetic industry have also been mentioned.

Controlling for openness in the male-dominated collaborative networks of the global film industry.

Studies of gender inequality in film industries have noted the persistence of male domination in creative roles (usually defined as director, producer, writer) and the slow pace of reform. Typical policy remedies are premised on aggregate counts of women as a proportion of overall industry participation. Network science offers an alternative way of identifying and proposing change mechanisms, as it puts emphasis on relationships instead of individuals. Preliminary work on applying network analysis to understand inequality in the film industry has been undertaken. However, in this study we offer a comprehensive approach that enables us to not only understand what inequality in the film industry looks like through the lens of network science but also how we can attempt to address this issue. We offer a data-driven simulation framework that investigates various what-if scenarios when it comes to network evolution. We then assess each of these scenarios with respect to its potential to address gender inequality in the film industry. As suggested by previous studies, inequality is exacerbated when industry networks are most closed. We review evidence from three different national film industries on network relationships in creative teams and identify a high proportion of men who only work with other men. In response to this observation, we test several mechanisms through which industry structures may generate higher levels of openness. Our results reveal that the most critical factor for improving network openness is not simply the statistical improvement of the number of women in a network, nor the removal of men who do not work with women. The most likely behavioural changes to a network will involve the production of connections between women and powerful men.

[Skill mix in medical and about medical professions]. / Krzyzujace sie kompetencje (skill mix) w zawodach medycznych i okolomedycznych.

An important problem faced by many healthcare systems is the shortage of medical staff, and in particular doctors and nurses. Their number, competences and qualifications determine the level of availability and quality of medical services. Unfortunately, the demand for medical services is increasing, along with the progressive aging of the population, as well as the increase in the incidence of chronic diseases and frequent reforms of health systems. Employee costs related to healthcare are the most burdensome for the system; therefore, based on the available resources, it is necessary to create effective teams of sector employees. This results in rationalizing employment, or providing new medical and about medical competencies to new groups of professionals, which gives rise to the skill mix phenomenon. A well-prepared and implemented skill mix contributes to improving the quality of patient care, increased patient satisfaction and better clinical outcomes. In the process of mixing of competences, the roles that have been exercised so far are being changed. While some professionals are expanding their existing roles, other employees are required to accept some aspects of the previous roles. In Poland, in order to counteract such negative trends (the shortage of doctors), changes have been introduced to increase access to medical services (e.g., nurses and midwives being vested with the right to issue prescriptions and medical ordinances, paramedics - with the right to perform medical emergency services and provide healthcare services, and physiotherapists - with the right to conduct independent physiotherapeutic visits). A new profession of a medical coordinator has also been introduced. Med Pr. 2020;71(3):337-52.