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Objective The aims of the study were: (1) to clarify the definitions of “migrant” used in occupational health research; (2) to summarize migrant workers’ industry sectors, occupations and employment conditions; (3) to identify the occupational health and safety services available to migrant workers; (4) to summarize work-related health problems found among migrant workers; (5) to identify the methodological challenges to research into occupational health of migrant workers; and (6) to recommend improvements in migrant occupational health research. Methods This position paper was prepared by researchers from several European countries and Australia, working within the EU COST Action OMEGA-NET. The paper drew on two recent systematic reviews on the occupational health of international migrant workers and other literature, and also identified uncertainties and gaps in the research literature. Migrants may, for example, be temporary or permanent, moving for specific jobs migrants or other reasons. Their ethnicity and language capabilities will affect their work opportunities. Results The occupational health literature seldom adequately identifies the heterogeneity or characteristics of the migrant group being studied. Migrants tend to work in more physically and mentally demanding environments with higher exposures than native workers. Migrants tend to have an increased risk of physical and mental ill health, but less access to health care services. This has been demonstrated recently by high rates of COVID-19 and less access to health care. There have been a number of cross-sectional studies of migrant health but few long-term cohort studies were identified. Other study designs, such as registry-based studies, surveys and qualitative studies may complement cross-sectional studies. Mixed-methodology studies would be valuable in research on migrants’ occupational health. Language and lack of trust are barriers to migrant research participation. Conclusion Targeted research, especially longitudinal, identifying how these economically important but often-vulnerable workers can be best assisted is needed. Researchers should identify the characteristics of the migrant workers that they are studying including visa/migration circumstances (temporary, permanent, undocumented), racial and ethnic characteristics, existing skills and language abilities.

Fraudulent papers from paper mills are a serious threat to the entire scientific community. Naunyn-Schmiedeberg’s Archives of Pharmacology has become the target of a massive attack of fraudulent papers originating from paper mills. This editorial highlights 20 important features we observed with paper mills and explains how the journal is responding to this serious threat to restore the integrity of science. Hopefully, this editorial is also helpful for editors of other scientific journals.

Urinary tract infections (UTIs) make up a significant proportion of the global burden of disease in vulnerable groups and tend to substantially impair the quality of life of those affected, making timely detection of UTIs a priority for public health. However, economic and societal barriers drastically reduce accessibility of traditional lab-based testing methods for critical patient groups in low-resource areas, negatively affecting their overall healthcare outcomes. As a result, cellulose-based materials such as paper and thread have garnered significant interest among researchers as substrates for so-called frugal analytical devices which leverage the material’s portability and adaptability for facile and reproducible diagnoses of UTIs. Although the field may be only in its infancy, strategies aimed at commercial penetration can appreciably increase access to more healthcare options for at-risk people. In this review, we catalogue recent advances in devices that use cellulose-based materials as the primary housing or medium for UTI detection and chart out trends in the field. We also explore different modalities employed for detection, with particular emphasis on their ability to be ported onto discreet casings such as sanitary products. Graphical abstract

The acute and long-lasting side effects of modern multimodal tumour therapy significantly impair quality of life and survival of patients afflicted with malignancies. The key components of this therapy include radiotherapy, conventional chemotherapy, immunotherapy and targeted therapies. In addition to established tumour therapy strategies, up to 30 new therapies are approved each year with only incompletely characterised side effects. This consensus paper discusses the risk factors that contribute to the development of a potentially adverse reaction to tumour therapy and, in addition, defines specific side effect profiles for different treatment groups. The focus is on novel therapeutics and recommendations for the surveillance and treatment of specific patient groups.

Multi-factor authentication (MFA) is a useful measure for strengthening authentication. Despite its security effectiveness, the adoption of MFA tools remains low. To create more human-centric authentication solutions, we designed and evaluated the efficacy of a risk-reduction-based incentivization model and implemented our proposed model in a large-scale organization with more than 92, 025 employees, and collected survey data from 287 participants and interviewed 41 participants. We observed negative perceptions and degraded understandings of MFA technology due to the absence of proper risk and benefit communication in the control group. Meanwhile, the experimental group employees showed positive perceptions of MFA use for their work and personal accounts. Our analysis and implementation strategy are critical for reducing users’ risks, creating positive security tool usage experiences, and motivating users to enhance their security practices.

To study the relationship between exposure to airborne particles in a pulp and paper mill and markers of inflammation and coagulation in blood. Personal sampling of inhalable dust was performed for 72 subjects working in a Swedish pulp and paper mill. Stationary measurements were used to study concentrations of total dust, respirable dust, PM10 and PM2.5, the particle surface area and the particle number concentrations. Markers of inflammation, interleukins (IL-1b, IL-6, IL-8, and IL-10), C-reactive protein (CRP), serum amyloid A (SAA), and fibrinogen and markers of coagulation factor VIII, von Willebrand, plasminogen activator inhibitor, and D-dimer were measured in plasma or serum. Sampling was performed on the last day of the work free period of 5 days, before and after the shift the first day of work and after the shifts the second and third day. In a mixed model analysis, the relationship between particulate exposures and inflammatory markers was determined. Sex, age, smoking, and BMI were included as covariates. The average 8-h time-weighted average (TWA) air concentration levels of inhalable dust were 0.30 mg/m(3), range 0.005-3.3 mg/m(3). The proxies for average 8-h TWAs of respirable dust were 0.045 mg/m(3). Significant and consistent positive relations were found between several exposure metrics (PM 10, total and inhalable dust) and CRP, SAA and fibrinogen taken post-shift, suggesting a dose-effect relationship. This study supports a relationship between occupational particle exposure and established inflammatory markers, which may indicate an increased risk of cardiovascular disease. Funding Agencies|Swedish Research Council for Health, Working Life and Welfare [2006-0152]

This open access White Paper details the status of hip and knee arthroplasty care in Germany. Hip and knee replacements are amongst the most frequently performed procedures and usually become necessarily due to age-related wear of the joint, osteoarthritis and fractures of the femoral neck. In light of demographic change, demands with regard to standards of care and the procedures are likely to rise.

GSMA is developing and standardizing specifications for embedded SIM cards with remote provisioning, called eUICCs, which are expected to revolutionize the cellular network subscription model. We study GSMA’s “Remote Provisioning Architecture for Embedded UICC” specification, which focuses on M2M devices, and we analyze the security of remote provisioning. Our analysis reveals weaknesses in the specification that would result in eUICCs being vulnerable to attacks: we demonstrate how a network adversary can exhaust an eUICC’s memory, and we identify three classes of attacks by malicious insiders that prevent service. We disclosed our findings to GSMA; GSMA confirmed the validity of these attacks and acknowledged their potential to disrupt the cellular industry. We propose fixes, which GSMA is incorporating into its specification. Thus, we improve security of next generation telecommunication networks.

Fraud victims are often refused a refund by their bank on the grounds that they failed to comply with their bank’s terms and conditions about PIN safety. We, therefore, conducted a survey of how many PINs people have, and how they manage them. We found that while only a third of PINs are ever changed, almost half of bank customers write at least one PIN down. We also found bank conditions that are too vague to test, or even contradictory on whether PINs could be shared across cards. Yet, some hazardous practices are not forbidden by many banks: of the 22.9% who re-use PINs across devices, half also use their bank PINs on their mobile phones. We conclude that many bank contracts fail a simple test of reasonableness, and ‘strong authentication’, as required by the Payment Services Directive II, should include usability testing.

We introduce a model for examining the factors that lead to the adoption of new encryption technologies. Building on the work of Brock and Durlauf, the model describes how agents make choices, in the presence of social interaction, between competing technologies given their relative cost, functionality, and usability. We apply the model to examples about the adoption of encryption in communication (email and messaging) and storage technologies (self-encrypting drives) and also consider our model’s predictions for the evolution of technology adoption over time.

This case study examines the European Transport White Paper of 2011 as an example of a planning domain application. The European Union is an economic and political union of some 28 states in Europe. Some of the key premises of the European Union have been to open up markets to free trade within the region and to seek to harmonise technical standards, laws, and processes to facilitate the free movement of people and goods. It is interesting that sustainability is also emphasized as an overarching goal for all areas of European policy making. The European Union employs a wide range of assessment and monitoring mechanisms to track progress on the implementation and performance of policies in the transport area, which is seen as a keystone for the so-called Single European Market. These mechanisms clearly reflect tensions between the different goals and pose challenges for the interpretation of indicators on transportation trends. Also the sheer size and complexity of the Union raises challenges for the effective application of indicator based evidence. The chapter will place the indicator- and application rich example of the ex ante assessment of the European Transport Policy White Paper in the wider context European Union policy making.

Background The main aim of emergency medical services (EMS) should be to provide universal emergency medical care which is EMS system available to all those who need it. Most of the developed countries have an integrated EMS system that is accessible by a single dial number in the whole country. Nepal does not have a proper EMS system. We conducted a literature review regarding methods of developing an integrated EMS system in Nepal. Result The fragmented system, high demand–low supply, inequity with the service, and inadequately trained responders are major problems associated with EMS in Nepal. Nepal too should develop an integrated single dial number EMS system to meet the current demand of EMS. Having a paramedic in ambulances as the first responders will prevent chaos and save critical time. Funding models have to be considered while developing an EMS considering the capital as well as operational cost. Conclusion Nepal can develop a public private partnership model of EMS where capital cost is provided by the government and operational cost by other methods. Community-based insurance system looks more feasible in a country like Nepal for generating operational cost.

Introduction In adults with a suspicion of peripheral bone infection, evidence-based guidelines in choosing the most accurate diagnostic strategy are lacking. Aim and methods To provide an evidence-based, multidisciplinary consensus document on the diagnostic management of adult patients with PBIs, we performed a systematic review of relevant infectious, microbiological, orthopedic, radiological, and nuclear medicine literature. Delegates from four European societies (European Bone and Joint Infection Society, European Society of Microbiology and Infectious Diseases, European Society or Radiology, and European Association of Nuclear Medicine) defined clinical questions to be addressed, thoroughly reviewed the literature pertinent to each of the questions, and thereby evaluated the diagnostic accuracy of each diagnostic technique. Inclusion of the papers per statement was based on a PICO (Population/problem – Intervention/indicator – Comparator – Outcome) question following the strategy reported by the Oxford Centre for Evidence-based Medicine. For each statement, the level of evidence was graded according to the 2011 review of the Oxford Centre for Evidence-based Medicine. All approved statements were addressed taking into consideration the available diagnostic procedures, patient acceptance, tolerability, complications, and costs in Europe. Finally, a commonly agreed-upon diagnostic flowchart was developed. Electronic supplementary material The online version of this article (10.1007/s00259-019-4262-x) contains supplementary material, which is available to authorized users.

Consumers are often willing to contribute their personal data for analytics projects that may create new insights into societal problems. However, consumers also have justified privacy concerns about the release of their data.

Publishing the results of your research is a fulfilling experience, both from a personal viewpoint, but also helping advance the orthopaedic knowledge. This chapter discusses the process from completing the study to formulating the final manuscript that is ready for submission, providing a structure to follow in preparation of the manuscript and tips on improving your writing style.

This Paper presents a bibliometric analysis of the papers published in the journal of Technology Enhanced Foreign Language Education (TEFLE), a core professional academic journal in China, during the years from 2006 to 2015. Our result aims to provide a clear view of the evolution of literature in the research field of technology enhanced foreign language learning over the past decade, intending to put forward a preliminary framework for TEFLE to improve its publication quality and at the same time foster better technology enhanced foreign language education in China. Bibliometric indicators of paper amount, author information, total citations, and frequency of keywords have been analyzed with the use of tools of BICOMB and SPSS and methods of co-word and cluster analysis, which indicates that, over the past decade, both of the quality of the published papers and the paper evaluation system has been improved. The statistics also reveal that the authors in TEFLE are mainly from eastern China, a research group that has been formed with more researchers constantly joining in, and a number of papers have been highly cited, bringing further interest in the related disciplines. Currently, the reform of foreign language classroom teaching with technological aids appears the hotspot topic in the related applied field. An effort is made to demonstrate that the research method has shifted to a new way that places equal emphasis on both quantitative and qualitative study in technology enhanced learning (TEL) and technologies have a bigger influence on foreign language learning in China, but in the meantime, there is an imbalance in the distribution of authors from different national geographic areas in TEL research.

Smart mobile devices process and store a vast amount of security- and privacy-sensitive data. To protect this data from malicious applications mobile operating systems, such as Android, adopt fine-grained access control architectures. However, related work has shown that these access control architectures are susceptible to application-layer privilege escalation attacks. Both automated static and dynamic program analysis promise to proactively detect such attacks. Though while state-of-the-art static analysis frameworks cannot adequately address native and highly obfuscated code, dynamic analysis is vulnerable to malicious applications using logic bombs to avoid early detection.

Two methods are described for homogentisic acid (HGA) determination in dried urine spots (DUS) on paper from Alkaptonuria (AKU) patients, devised for quick early diagnosis. AKU is a rare autosomal recessive disorder caused by deficiency of homogentisate 1,2-dioxygenase, yielding in accumulation of HGA. Its massive excretion causes urine darkening by exposure to air or alkalinization, and is a diagnostic marker. The deposition of polymers produced after HGA oxidation within the connective tissues causes ochronotic arthritis, a degenerative joint disease manifesting in adulthood and only rarely in childhood. No early diagnosis is usually accomplished, awareness following symptom development.Two methods were designed for HGA determination in DUS: (1) a rapid semi-quantitative reliable method based on colour development in alkali and quantification by comparison with dried paper spots from HGA solutions of known concentration and (2) a quantitative and sensitive HPLC-linked method, previously devised for purine and pyrimidine analysis in urine and plasma.Colour intensity developed by DUS after alkali addition was proportional to HGA concentration, and calculated amounts were in good agreement with quantitative analysis performed by RP-HPLC on DUS and on urines as such.DUS, often used for different diagnostic purpose, are easily prepared and safely delivered. The simple and quick colour method proposed provides reliable HGA assessment and is fit for large screening. HGA concentration determined in 10 AKU patient DUS by both methods 1 and 2 was in agreement with direct urine assay and in the range reported by literature.A reliable HGA quantification based on colour development in paper urine spots is validated by HPLC-linked HGA quantification, and proposed as a quick diagnostic tool for AKU patients.

The mission of theoretical cryptography is to define and construct provably secure cryptographic protocols and schemes. Without proofs of security, cryptographic constructs offer no guarantees whatsoever and no basis for evaluation and comparison. As most security proofs necessarily come in the form of a reduction between the security claim and an intractability assumption, such proofs are ultimately only as good as the assumptions they are based on. Thus, the complexity implications of every assumption we utilize should be of significant substance, and serve as the yard stick for the value of our proposals. Lately, the field of cryptography has seen a sharp increase in the number of new assumptions that are often complex to define and difficult to interpret. At times, these assumptions are hard to untangle from the constructions which utilize them. We believe that the lack of standards of what is accepted as a reasonable cryptographic assumption can be harmful to the credibility of our field. Therefore, there is a great need for measures according to which we classify and compare assumptions, as to which are safe and which are not. In this paper, we propose such a classification and review recently suggested assumptions in this light. This follows the footsteps of Naor Crypto 2003. Our governing principle is relying on hardness assumptions that are independent of the cryptographic constructions.

The ScienceWISE system is a collaborative ontology editor and paper annotation tool designed to help researchers in their discovery. In this paper, we describe the system currently deployed at sciencewise.info and the exposition of its data as Linked Data. During the “RDFization” process, we faced issues to encode the knowledge base in SKOS and find resources to link to on the LOD. We discuss these issues and the remaining open challenges to implement some target features.

Up to the twenty-first century, paper is still widely adopted for recording and reading. However, paper-based materials are fully capable of presenting abstract concepts and complicated knowledge with static text and figures. Learners usually need timely and adequate supports when encountering difficulties during learning. With a consideration of applying technologies, the learning tool must have a certain mobility and accessibility for acquiring facilitative resources. Using the networking capability of smartphone to access digital content from the Internet to enrich conventional paper-based learning activities is worth investigating. This chapter introduces an augmentation-enhanced learning context with an integration of digital content into paper-based materials in order to facilitate learning. Constructive feedback, scaffolding questioning, and procedural scaffolding are three strategies applied into the instructional designs and learning system. Quasi-experiments for personal learning and collaborative learning were also conducted to evaluate the effects on learning performance. The results suggest that the three instructional designs had significantly positive effects on individual’s learning performance. Team’s learning performance and team’s discourse levels were promoted as well. This chapter lays out a strong foundation for researchers to further explore how to better design different learning strategies for different learning subjects in the augmentation-enhanced learning context using smartphones. It is hoped that educational practitioners are able to obtain concrete ideas and solutions on how to better leverage the benefits of both paper-based content and digital learning materials in a real blended learning environment.

SVM is a new general learning method based on the statistic learning system which can be used as an effective means to process small sample, nonlinear and high dimensional pattern recognition. This paper did research on the learning algorithm of support vector machine, extracted characteristic data of banknote which is on account of PCA according to the characteristics of the support vector machine (SVM), and proposed to put support vector machine (SVM) into banknotes denomination recognition by combining SMO training algorithm with one-to-many multi-value classification algorithm. Besides, this article used genetic algorithm in parameters optimization such as the punishment coefficient C of soft margin SVM and the width parameter of Gaussian kernel function. The ultimate purpose is to recognize the denomination of banknote efficiently and accurately. The experimental results verified that this kind of recognition method increases the recognition accuracy up to 90% or more.

Business Process Management (BPM) (Dumas et al. 2013) investigates how organizations function and can be improved on the basis of their business processes. The starting point for BPM is that organizational performance is a function of process performance. Thus, BPM proposes a set of methods, techniques and tools to discover, analyze, implement, monitor and control business processes, with the ultimate goal of improving these processes. Most importantly, BPM is not just an organizational management discipline. BPM also studies how technology, and particularly information technology, can effectively support the process improvement effort. In the past two decades the field of BPM has been the focus of extensive research, which spans an increasingly growing scope and advances technology in various directions. The main international forum for state-of-the-art research in this field is the International Conference on Business Process Management, or “BPM” for short—an annual meeting of the aca ...

In this world of digital and social media booms, a number of people spend their valuable times burying heads in smartphones, resulting in unintentional increased gaps in physical relationship with people nearby. A hybrid digital-physical medium is a possible solution for this problem by means of externalizing social media data and integrating them into a physical medium somehow. In this way, using social media will simultaneously connect us with both virtual and physical worlds.

How did Britons view China in 2020, at the height of the Covid-19 pandemic? This paper presents new, detailed evidence of the negative and worsening perceptions of China in the UK across three domains: public opinion (based on survey data collected in autumn 2020), political elites in parliament, and the media. The worsening of perceptions of China emerged in the context of a changing and more contested China policy from the UK government and a greater level of public debate about China, partly a consequence of the onset of the Covid-19 pandemic. The paper places analysis of these perceptions in the context of the development of relations between the UK and China. Together with deteriorating Chinese views of the UK's China policy and controversy over a number of developments in China, widespread negative views about China among the British public and in political circles will constrain UK-China relations from developing in a more positive direction.

Purpose The development of assistive technologies that support people in social interactions has attracted increased attention in HCI. This paper presents a systematic review of studies of Socially Assistive Systems targeted at older adults and people with disabilities. The purpose is threefold: (1) Characterizing related assistive systems with a special focus on the system design, primarily including HCI technologies used and user-involvement approach taken; (2) Examining their ways of system evaluation; (3) Reflecting on insights for future design research. Methods A systematic literature search was conducted using the keywords “social interactions” and “assistive technologies” within the following databases: Scopus, Web of Science, ACM, Science Direct, PubMed, and IEEE Xplore. Results Sixty-five papers met the inclusion criteria and were further analyzed. Our results showed that there were 11 types of HCI technologies that supported social interactions for target users. The most common was cognitive and meaning understanding technologies, often applied with wearable devices for compensating users’ sensory loss; 33.85% of studies involved end-users and stakeholders in the design phase; Four types of evaluation methods were identified. The majority of studies adopted laboratory experiments to measure user-system interaction and system validation. Proxy users were used in system evaluation, especially in initial experiments; 42.46% of evaluations were conducted in field settings, primarily including the participants’ own homes and institutions. Conclusion We contribute an overview of Socially Assistive Systems that support social interactions for older adults and people with disabilities, as well as illustrate emerging technologies and research opportunities for future work.

This paper discusses the scope for international macroprudential policy coordination in a financially integrated world economy. It begins with a review of the transmission channels associated with, and the empirical evidence on, financial spillovers and spillbacks. Limitations of the existing literature are also identified. The potential gains associated with cross-border macroprudential coordination, dwelling on both recent analytical contributions and quantitative studies based on multi-country models with financial frictions, are then evaluated. The issue of whether coordination of macroprudential policies simultaneously requires some degree of monetary policy coordination is also discussed. The analysis focuses on the potential for policy coordination between major advanced economies and a group identified as systemically-important middle-income countries (SMICs). Next, practical ways to promote international macroprudential policy coordination are considered. Following a discussion of Basel III’s Principle of reciprocity and ways to improve it, the paper advocates a further strengthening of the current statistical, empirical and analytical work conducted by international financial institutions to evaluate, and raise awareness of, the gains from international coordination of macroprudential policies.

In recent years, there has been a growing interest in the use of reference conceptual models to capture information about complex and sensitive business domains (e.g., finance, healthcare, space). These models play a fundamental role in different types of critical semantic interoperability tasks. Therefore, domain experts must be able to understand and reason with their content. In other words, these models need to be cognitively tractable. This paper contributes to this goal by proposing a model clustering technique that leverages on the rich semantics of ontology-driven conceptual models (ODCM). In particular, we propose a formal notion of Relational Context to guide the automated clusterization (or modular breakdown) of conceptual models. Such Relational Contexts capture all the information needed for understanding entities "qua players of roles" in the scope of an objectified (reified) relationship (relator). The paper also presents computational support for automating the identification of Relational Contexts and this modular breakdown procedure. Finally, we report the results of an empirical study assessing the cognitive effectiveness of this approach.

This paper explores the impact of infrastructure on trade connectivity among ASEAN and three Asian countries—India, China, and Japan. Our study is mainly motivated by the increased infrastructure investment and trade among these countries in recent years. The main results of trade network analysis include high trade density and interconnectedness among ASEAN, India, China, and Japan. There are specific “trade intensive paths” among the few countries in the group. It highlights the “export hubs” or main “suppliers of intermediate goods” in the region. Further, the paper analyzed the nexus between trade connectivity and infrastructure by applying the panel fixed effects method and Poisson pseudo-maximum likelihood. Moreover, the robustness of the results is tested by estimating two-stage least square. Hard infrastructure, foreign direct investment plays a crucial role in bringing the nexus to trade connectivity. Reducing trade barriers and improving infrastructure quality are essential for deepening regional trade integration.

Coronavirus disease 2019 (COVID-19) pandemic is currently a serious global health threat. While conventional laboratory tests such as quantitative real-time polymerase chain reaction (qPCR), serology tests, and chest computerized tomography (CT) scan allow diagnosis of COVID-19, these tests are time-consuming and laborious, and are limited in resource-limited settings or developing countries. Point-of-care (POC) biosensors such as chip-based and paper-based biosensors are typically rapid, portable, cost-effective, and user-friendly, which can be used for COVID-19 in remote settings. The escalating demand for rapid diagnosis of COVID-19 presents a strong need for a timely and comprehensive review on the POC biosensors for COVID-19 that meet ASSURED criteria: Affordable, Sensitive, Specific, User-friendly, Rapid and Robust, Equipment-free, and Deliverable to end users. In the present review, we discuss the importance of rapid and early diagnosis of COVID-19 and pathogenesis of COVID-19 along with the key diagnostic biomarkers. We critically review the most recent advances in POC biosensors which show great promise for the detection of COVID-19 based on three main categories: chip-based biosensors, paper-based biosensors, and other biosensors. We subsequently discuss the key benefits of these biosensors and their use for the detection of antigen, antibody, and viral nucleic acids. The commercial POC biosensors for COVID-19 are critically compared. Finally, we discuss the key challenges and future perspectives of developing emerging POC biosensors for COVID-19. This review would be very useful for guiding strategies for developing and commercializing rapid POC tests to manage the spread of infections.Graphical abstract.

Emerging intelligent environments are considered to offer significant opportunities to positively impact human life, both at an individual and at a societal level, and in particular to provide useful means to support people in their daily life activities and thus improve well-being for everybody, especially for older people and for people with limitations of activities. In this context, accessibility and usability, although necessary, are not sufficient to ensure that applications and services are appropriately designed to satisfy human needs and overcome potential functional limitations in the execution of everyday activities fundamental for well-being. This position paper puts forward the claim that, in order to achieve the above objective, it is necessary that: (i) the design of Assistive Intelligent Environments is centered around the well-being of people, roughly intended as the possibility of executing the (everyday) human activities necessary for living (independently), thus emphasizing usefulness in addition to usability; (ii) the technological environment is orchestrated around such activities and contains knowledge about how they are performed and how people need to be supported to perform them; (iii) the environment makes use of monitoring and reasoning capabilities in order to adapt, fine-tune and evolve over time the type and level of support provided, and this process takes place considering ethical values; (iv) the applications must also support the possibility of contact with other people, who in many cases may be the only effective help. Moving forward from the Design for All paradigm, this paper discusses how the latter can be revisited under the perspective of technology’s usefulness and contribution to human well-being. Subsequently, it introduces a practical notion of well-being based on the ICF classification of human functions and activities and discusses how such notion can constitute the starting point and the focus of design approaches targeted to assist people in their everyday life mainly (but not exclusively) in the home environment. As a subsequent step, the need for integrating Artificial Intelligence capabilities in assistive intelligent environments is discussed, based on the complexity of the human problems to be addressed and the diversity of the types of support needed. The proposed approach is exemplified and illustrated through the experience acquired in the development of four applications, addressing vital aspects of human life, namely nutrition, stress management, sleep management and counteracting loneliness. Finally, based on the acquired experience, the need to take into account ethical values in the development of assistive intelligent environments is discussed.

Online learning has become one of the most important learning styles, yet with the need of supervisors to consistently keep the learners motivated and on-task. Some learners could be supervised by outer factors, and distance learners have to be motivated by themselves. However, online learning engagement is hardly to be assessed by supervisors in real time. With the rapid development of information technology, it is able to remedy the above problem by using intelligent video surveillance techniques. In this paper, we propose a novel framework of learning engagement assessment which introduces facial expression recognition to timely acquire the emotional changes of the learners. Moreover, a new facial expression recognition method is proposed based on domain adaptation, which is suitable for the MOOC scenario. The experiments show the effectiveness of our proposed framework on assessing learners’ learning engagement. The comparisons with the state-of-the-art methods also demonstrate the superiority of our proposed facial emotion recognition method.

Within the elderly population, psychogeriatric patients may be particularly susceptible to negative mental health effects of the coronavirus crisis. Detailed information about the psychosocial well-being of psychogeriatric patients during the pandemic is still sparse. Here we examined which aspects of subjective experience of the COVID-19 pandemic especially affect levels of depression, anxiety and quality of life in psychogeriatric patients with and without cognitive impairment. A cross-sectional paper survey was conducted during the first German lockdown among patients with a diagnosed psychiatric disorder (≥ 60 years) or a diagnosed neurodegenerative disease (regardless of their age) from the department for neurodegenerative diseases and geriatric psychiatry at the University of Bonn. The WHO-5-, GAD-7- and WHOQOL-old score were used to determine levels of depression, anxiety and quality of life. The second part obtained information about the subjective experience of the COVID-19 pandemic. Statistical analysis included among others principal component analysis and multiple linear regression analysis. COVID-19-related, immediate distress was a strong predictor of elevated symptoms of depression, anxiety and a reduced quality of life. COVID-19-related concerns regarding health and financial security, however, were not significantly associated with negative mental health outcomes. The overall prevalence of symptoms of depression (50.8% [95% CI 43.8–57.6%]) and anxiety (32.7% [95% CI 26.4–39.2%]) among psychogeriatric patients was high. Our findings indicate that psychogeriatric patients are not significantly affected by COVID-19-related concerns but are primarily suffering from emotional consequences resulting from changed living conditions due to the pandemic. Supplementary Information The online version contains supplementary material available at 10.1007/s00406-021-01340-1.

This paper studies the perceived difficulty of recruiting scarce competencies to rural regions. Furthermore, the role of policy in facilitating and enhancing recruitment to and better skills matching in rural regions is discussed. Based on a survey targeted to the business sections of Swedish municipalities, the results show that recruitment is perceived to be difficult in both rural and nonrural regions and that the difficulty of recruiting for the right skills results in a lack of skills matching and constitutes an obstacle to growth. Rural regions located close to urban areas can to some extent mitigate these recruitment problems, and their locations pose less of a barrier in recruitment processes compared to those of remotely located rural regions.Which policies can help remedy recruitment problems faced in rural regions? In both rural and nonrural regions, incentives for writing off student debt and relocation support for accompanying persons and tandem recruitment are perceived to be the most promising policies. Rural regions are more receptive to the implementation of such policies. Finally, the need for flexibility and policies that can be adapted to the regional demand for labour are stressed.

The aim of this paper is to examine generic competition in the UK, with a special focus on the role of Health Technology Assessment (HTA) on generic market entry and diffusion. In the UK, where no direct price regulation on pharmaceuticals exists, HTA has a leading role for recommending the use of medicines providing a non-regulatory aspect that may influence the dynamics in the generic market. The paper focuses on the role of Technology Appraisals issued by the National Institute for Health and Care Excellence (NICE). We follow a two-step approach. First, we examine the probability of generic entry. Second, conditional on generic entry, we examine the determinants of generic market share. We use data from IQVIA British Pharmaceutical Index (BPI) for the primary care market for 60 products that lost patent between 2003 and 2012. Our results suggest that market size remains one of the main drivers of generic entry. After controlling for market size, intermolecular substitution and difficulty of manufacturing increase the likelihood of generic entry. After generic entry, our estimates suggest that generic market share is highly state dependent. Our findings also suggest that while NICE recommendations do influence generic uptake, there is only marginal evidence they affect generic entry.

The COVID-19 has been a worldwide pandemic and it needs for studies related to effect on people's demand for insurance during the pandemic which is an important way to transfer risk. However, there is a lack of research linking COVID-19 and people's demand for insurance. The objective of this paper is to investigate the impact of COVID-19 pandemic on issuance demand, using data covering 241 cities on confirmed COVID-19 cases and insurance company revenue in China. The empirical results show that more confirmed COVID-19 cases are associated with greater per capita insurance revenue and the results are robust when considering endogeneity concern. Economically, the per capita insurance revenue increases by 0.896 Yuan for each more confirmed case. In terms of insurance type, the greatest increased insurance revenue is for life insurance, followed by health insurance. We further consider the heterogeneity of regions and find that the impact of COVID-19 on insurance revenue only exists in regions with worse medical treatment conditions or higher medical burden.

Background Accelerated by the coronavirus disease 2019 (Covid-19) pandemic, major and lasting changes are occuring in healthcare structures, impacting people's experiences and value creation in all aspects of their lives. Information systems (IS) research can support analysing and anticipating resulting effects. Aim The purpose of this study is to examine in what areas health information systems (HIS) researchers can assess changes in healthcare structures and, thus, be prepared to shape future developments. Method A hermeneutic framework is applied to conduct a literature review and to identify the contributions that IS research makes in analysing and advancing the healthcare industry. Results We draw an complexity theory by borrowing the concept of 'zooming-in and out', which provides us with a overview of the current, broad body of research in the HIS field. As a result of analysing almost 500 papers, we discovered various shortcomings of current HIS research. Contribution We derive future pathways and develop a research agenda that realigns IS research with the transformation of the healthcare industry already under way.

This paper aims to explore various possibilities in the evolving global gas market by constructing game-theoretical models involving the major players: Russia and Qatar exporting gas to the Asia-Pacific and Europe, respectively. We explore a series of hypothetical scenarios based on competitive and collusive settings for the Asia-Pacific LNG market and based on Qatar's export route to the European gas market. The scenarios that are examined are (1) Russia as the follower and Qatar as the leader in a Stackelberg game; (2) Russia and Qatar as Cournot competitors; (3) collaboration between Russia and Qatar as bilateral monopolies; (4) Qatar exporting gas to European borders; (5) Qatar exporting gas to the last transit country; and (6) Qatar transporting gas to the Turkish border under a multi-pricing scheme. Demand is estimated under each scenario to simulate the respective export volumes, prices and quantities, and profit in each scenario. By exploring these market interactions, we find that it is essential for Russia to strike a deal with Qatar in the Asian market and accelerate their gas production in order to compete as an LNG market leader. Russia is likely to benefit more if it can link with Qatar to act as a monopoly on their segmental demand curve. On the other hand, Qatar's profit is expected to be higher under the scenario when Qatar sells all the gas to the last transit country as the sole demand point instead of passing through transit countries.

In the era of autonomous robots, multi-targets search methods inspired researchers to develop adapted algorithms to robot constraints, and with the rising of Swarm Intelligence (SI) approaches, Swarm Robotics (SRs) became a very popular topic. In this paper, the problem of searching for an exponentially increasing number of targets in a complex and unknown environment is addressed. Our main objective is to propose a Robotic target search strategy based on the EHO (Elephants Herding Optimization) algorithm, namely Robotic-EHO (REHO). The main additions were the collision-free path planning strategy, the velocity limitation, and the extension to the multi-target version in discrete environments. The proposed method has been the subject of many experiments, emulating the search of infected individuals by COVID-19 in a context of containment within complex and unknown random environments, as well as in the real case study of USA. The particularity of these environments is their increasing targets' number and the dynamic Containment Rate (CR) that we propose. The experimental results show that REHO reacts much better in high Containment Rate, early start search mission, and where the robots' speed is higher than the virus spread speed.

COVID-19 is an acronym for coronavirus disease 2019. Initially, it was called 2019-nCoV, and later International Committee on Taxonomy of Viruses (ICTV) termed it SARS-CoV-2. On 30th January 2020, the World Health Organization (WHO) declared it a pandemic. With an increasing number of COVID-19 cases, the available medical infrastructure is essential to detect the suspected cases. Medical imaging techniques such as Computed Tomography (CT), chest radiography can play an important role in the early screening and detection of COVID-19 cases. It is important to identify and separate the cases to stop the further spread of the virus. Artificial Intelligence can play an important role in COVID-19 detection and decreases the workload on collapsing medical infrastructure. In this paper, a deep convolutional neural network-based architecture is proposed for the COVID-19 detection using chest radiographs. The dataset used to train and test the model is available on different public repositories. Despite having the high accuracy of the model, the decision on COVID-19 should be made in consultation with the trained medical clinician.

In this paper, linear regression (LR), multi-linear regression (MLR) and polynomial regression (PR) techniques are applied to propose a model Li-MuLi-Poly. The model predicts COVID-19 deaths happening in the United States of America. The experiment was carried out on machine learning model, minimum mean square error model, and maximum likelihood ratio model. The best-fitting model was selected according to the measures of mean square error, adjusted mean square error, mean square error, root mean square error (RMSE) and maximum likelihood ratio, and the statistical t-test was used to verify the results. Data sets are analyzed, cleaned up and debated before being applied to the proposed regression model. The correlation of the selected independent parameters was determined by the heat map and the Carl Pearson correlation matrix. It was found that the accuracy of the LR model best-fits the dataset when all the independent parameters are used in modeling, however, RMSE and mean absolute error (MAE) are high as compared to PR models. The PR models of a high degree are required to best-fit the dataset when not much independent parameter is considered in modeling. However, the PR models of low degree best-fits the dataset when independent parameters from all dimensions are considered in modeling.

Graphical Abstract Eco-innovations are innovations capable of helping to reduce the environmental impacts of production processes. In this sense, the adoption of models that assess comprehensively, in an integrated manner and in different perspectives, the general performance of these innovations allows managers to guide their decisions. The object of this research is the use of an eco-innovation in the production processes of cassava, where the waste generated is treated by biodigesters. These cassava processing industries are located in southern Brazil, Paraná State, comprising a multiple case study. A literature review was also carried out to propose a set of indicators capable of assessing the overall impact of this eco-innovation in eight lines of action: (1) environmental, (2) social, (3) economic, (4) human resource training, (5) institutional development, (6) introduction of innovation, (7) unwanted occurrences, and (8) characteristics of environmental management. To compile and process the data, the computerized model INOVA-tec System was used. The objective was to employ the INOVA-tec System model as an instrument for evaluating eco-innovative processes in leading companies in its segment, looking for evidence to expand its usability to other realities in the agro-industry. The results show that the technology scenario is favorable to its dissemination; however, the low performance of the indicators together makes it underutilized.

Telehealth drastically reduces the time burden of appointments and increases access to care for homebound patients. During the COVID-19 pandemic, many outpatient practices closed, requiring an expansion of telemedicine capabilities. However, a significant number of patients remain unconnected to telehealth-capable patient portals. Currently, no literature exists on the success of and barriers to remote enrollment in telehealth patient portals. From March 26 to May 8, 2020, a total of 324 patients were discharged from Mount Sinai Beth Israel (MSBI), a teaching hospital in New York City. Study volunteers attempted to contact and enroll patients in the MyChart patient portal to allow the completion of a post-discharge video visit. If patients were unable to enroll, barriers were documented and coded for themes. Of the 324 patients discharged from MSBI during the study period, 277 (85%) were not yet enrolled in MyChart. Volunteers successfully contacted 136 patients (49% of those eligible), and 39 (14%) were successfully enrolled. Inability to contact patients was the most significant barrier. For those successfully contacted but not enrolled, the most frequent barrier was becoming lost to follow-up (29% of those contacted), followed by lack of interest in remote appointments (21%) and patient technological limitations (9%). Male patients, and those aged 40–59, were significantly less likely to successfully enroll compared to other patients. Telehealth is critical for healthcare delivery. Remote enrollment in a telemedicine-capable patient portal is feasible, yet underperforms compared to reported in-person enrollment rates. Health systems can improve telehealth infrastructure by incorporating patient portal enrollment into in-person workflows, educating on the importance of telehealth, and devising workarounds for technological barriers.

Regulation has not been a primary focus of research within the information systems discipline or the research domain of electronic markets. A framework is presented to support understanding of the field. A review of published works has established that many research opportunities exist. The usefulness of the framework is validated by means of an examination of the platform-based business sector, with particular reference to Uber.

Purpose We aimed to estimate the structure of internalizing and externalizing symptoms and potential time dynamics in their association. This is understudied among adolescents, despite increasing internalizing and decreasing externalizing symptoms in recent years. Methods We analyzed data from US Monitoring the Future cross-sectional surveys (1991–2018) representative of school-attending adolescents (N = 304,542). Exploratory factor analysis using maximum likelihood estimation method and promax rotation resulted in a two-factor solution (factor correlation r = 0.24) that differentiated eight internalizing and seven conduct-related externalizing symptoms. Time-varying effect modification linear regression models estimated the association between standardized internalizing and externalizing symptoms factor scores over time overall and by gender. Results In 2012, trends in average factor scores diverged for internalizing and externalizing factors. The average standardized internalizing factor score increased from − 0.03 in 2012 to 0.06 in 2013 and the average externalizing factor score decreased from − 0.06 in 2011 to − 0.13 in 2012. We found that for every one-unit increase in standardized internalizing factor score, standardized externalizing factor score increased by 0.224 units in 2010 (95% CI: 0.215, 0.233); the magnitude of this increase was 22.3% lower in 2018 (i.e., 0.174 units; 95% CI: 0.160, 0.188). Decoupling of internalizing and externalizing symptoms began earlier among boys (~ 1995) than among girls (~ 2010). Conclusion The decoupling of internalizing and externalizing symptoms among adolescents suggests that changes in the prevalence of shared risk factors for adolescent psychiatric symptoms affect these dimensions in opposing directions, raising the importance of considering symptoms and their risk factors together in prevention and intervention efforts. Supplementary Information The online version contains supplementary material available at 10.1007/s00127-021-02189-4.

Alpha synuclein has a key role in the pathogenesis of Parkinson’s disease (PD), Dementia with Lewy Bodies (LBD) and Multiple System Atrophy (MSA). Immunotherapies aiming at neutralising toxic αSyn species are being investigated in the clinic as potential disease modifying therapies for PD and other synucleinopathies. In this study, the effects of active immunisation against αSyn with the UB-312 vaccine were investigated in the Thy1SNCA/15 mouse model of PD. Young transgenic and wild-type mice received an immunisation regimen over a period of 6 weeks, then observed for an additional 9 weeks. Behavioural assessment was conducted before immunisation and at 15 weeks after the first dose. UB-312 immunisation prevented the development of motor impairment in the wire test and challenging beam test, which was associated with reduced levels of αSyn oligomers in the cerebral cortex, hippocampus and striatum of Thy1SNCA/15 mice. UB-312 immunotherapy resulted in a significant reduction of theαSyn load in the colon, accompanied by a reduction in enteric glial cell reactivity in the colonic ganglia. Our results demonstrate that immunisation with UB-312 prevents functional deficits and both central and peripheral pathology in Thy1SNCA/15 mice. Supplementary Information The online version contains supplementary material available at 10.1007/s00401-021-02381-5.

Little is known about the relationship of COVID-19 outcomes with onychomycosis. We investigated the relationship of onychomycosis with COVID-19 outcomes. A retrospective cohort study was performed on SARS-CoV-2 positive adult outpatients or inpatients who had onychomycosis and other skin diseases. Overall, 430 adults were identified with SARS-CoV-2 and a skin disease, including 98 with diagnosed onychomycosis. In bivariable logistic regression models, onychomycosis was associated with increased hospitalization {odds ratio(OR) [95% confidence interval (CI)]: 3.56 [2.18-5.80]}, initial inpatient vs. outpatient visits (OR [95% CI]: 2.24 [1.35-3.74]), use of oxygen therapy (OR [95% CI]: 2.77 [1.60-4.79]), severe-critical vs. asymptomatic-mild severity (OR [95% CI]: 2.28 [1.32-3.94]), and death (OR [95% CI]: 7.48 [1.83-30.47]) from COVID-19, but not prolonged hospitalization (OR [95% CI]: 1.03 [0.47-2.25]). In multivariable models adjusting for socio-demographics, comorbidities, and immunosuppressant medication use, the associations with onychomycosis remained significant for hospitalization, inpatient visits, oxygen therapy, severe-critical COVID-19. Onychomycosis was a significant independent risk factor for COVID-19 severity, hospitalization, and receiving supplemental oxygen therapy.

This paper analyses how recent trends in heat waves impact heat warning systems. We performed a retrospective analysis of the challenges faced by the French heat prevention plan since 2004. We described trends based on the environmental and health data collected each summer by the French heat warning system and prevention plan. Major evolutions of the system were tracked based on the evaluations organized each autumn with the stakeholders of the prevention plan. Excess deaths numbering 8000 were observed during heat waves between 2004 and 2019, 71% of these between 2015 and 2019. We observed major changes in the characteristics, frequency and the geographical spread of heat waves since 2015. Feedbacks led to several updates of the warning system such as the extension of the surveillance period. They also revealed that risk perception remained limited among the population and the stakeholders. The sharp increase in the number of heat warnings issued per year since 2015 challenges the acceptability of the heat warnings. Recent heat waves without historical equivalent interfere with the development of evidence-based prevention strategies. The growing public health impacts heat waves emphasize the urgent need to act to adapt the population, at different levels of intervention, from individual comportments to structural modifications. A specific attention should be given to increase the resources allocated to the evaluation and the management of heat-related risks, especially considering the needs to catch with the rapid rhythm of the changing climate. Supplementary Information The online version contains supplementary material available at 10.1007/s00484-021-02123-y.