Design and evaluation of a scalable Internet of Things backend for smart ports

Internet of Things (IoT) technologies, when adequately integrated, cater for logistics optimisation and operations' environmental impact monitoring, both key aspects for today's EU ports management. This article presents Obelisk, a scalable and multi-tenant cloud-based IoT integration platform used in the EU H2020 PortForward project. The landscape of IoT protocols being particularly fragmented, the first role of Obelisk is to provide uniform access to data originating from a myriad of devices and protocols. Interoperability is achieved through adapters that provide flexibility and evolvability in protocol and format mapping. Additionally, due to ports operating in a hub model with various interacting actors, a second role of Obelisk is to secure access to data. This is achieved through encryption and isolation for data transport and processing, respectively, while user access control is ensured through authentication and authorisation standards. Finally, as ports IoTisation will further evolve, a third need for Obelisk is to scale with the data volumes it must ingest and process. Platform scalability is achieved by means of a reactive micro-services based design. Those three essential characteristics are detailed in this article with a specific focus on how to achieve IoT data platform scalability. By means of an air quality monitoring use-case deployed in the city of Antwerp, the scalability of the platform is evaluated. The evaluation shows that the proposed reactive micro-service based design allows for horizontal scaling of the platform as well as for logarithmic time complexity of its service time

Scalable fleet monitoring and visualization for smart machine maintenance and industrial IoT applications

The wide adoption of smart machine maintenance in manufacturing is blocked by open challenges in the Industrial Internet of Things (IIoT) with regard to robustness, scalability and security. Solving these challenges is of uttermost importance to mission-critical industrial operations. Furthermore, effective application of predictive maintenance requires well-trained machine learning algorithms which on their turn require high volumes of reliable data. This paper addresses both challenges and presents the Smart Maintenance Living Lab, an open test and research platform that consists of a fleet of drivetrain systems for accelerated lifetime tests of rolling-element bearings, a scalable IoT middleware cloud platform for reliable data ingestion and persistence, and a dynamic dashboard application for fleet monitoring and visualization. Each individual component within the presented system is discussed and validated, demonstrating the feasibility of IIoT applications for smart machine maintenance. The resulting platform provides benchmark data for the improvement of machine learning algorithms, gives insights into the design, implementation and validation of a complete architecture for IIoT applications with specific requirements concerning robustness, scalability and security and therefore reduces the reticence in the industry to widely adopt these technologies

The Neutrophil Life Cycle.

Neutrophils are recognized as an essential part of the innate immune response, but an active debate still exists regarding the life cycle of these cells. Neutrophils first differentiate in the bone marrow through progenitor intermediaries before entering the blood, in a process that gauges the extramedullary pool size. Once believed to be directly eliminated in the marrow, liver, and spleen, neutrophils, after circulating for less than 1 day, are now known to redistribute into multiple tissues with poorly understood kinetics. In this review, we provide an update on the dynamic distribution of neutrophils across tissues in health and disease, and emphasize differences between humans and model organisms. We further highlight issues to be addressed to exploit the unique features of neutrophils in the clinic

Outcome in patients perceived as receiving excessive care across different ethical climates: a prospective study in 68 intensive care units in Europe and the USA

Purpose: Whether the quality of the ethical climate in the intensive care unit (ICU) improves the identification of patients receiving excessive care and affects patient outcomes is unknown. Methods: In this prospective observational study, perceptions of excessive care (PECs) by clinicians working in 68 ICUs in Europe and the USA were collected daily during a 28-day period. The quality of the ethical climate in the ICUs was assessed via a validated questionnaire. We compared the combined endpoint (death, not at home or poor quality of life at 1 year) of patients with PECs and the time from PECs until written treatment-limitation decisions (TLDs) and death across the four climates defined via cluster analysis. Results: Of the 4747 eligible clinicians, 2992 (63%) evaluated the ethical climate in their ICU. Of the 321 and 623 patients not admitted for monitoring only in ICUs with a good (n = 12, 18%) and poor (n = 24, 35%) climate, 36 (11%) and 74 (12%), respectively were identified with PECs by at least two clinicians. Of the 35 and 71 identified patients with an available combined endpoint, 100% (95% CI 90.0–1.00) and 85.9% (75.4–92.0) (P = 0.02) attained that endpoint. The risk of death (HR 1.88, 95% CI 1.20–2.92) or receiving a written TLD (HR 2.32, CI 1.11–4.85) in patients with PECs by at least two clinicians was higher in ICUs with a good climate than in those with a poor one. The differences between ICUs with an average climate, with (n = 12, 18%) or without (n = 20, 29%) nursing involvement at the end of life, and ICUs with a poor climate were less obvious but still in favour of the former. Conclusion: Enhancing the quality of the ethical climate in the ICU may improve both the identification of patients receiving excessive care and the decision-making process at the end of life

Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial.

Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

FLINT : flows for the Internet of Things

New protocols and technologies are continuously competing in the Internet of Things. This has resulted in a fragmented landscape that complicates the integration of different solutions. Standardization efforts try to avoid this problem, however within a certain ecosystem, multiple standards still require integration to enable trans-sector innovation. Moreover, existing devices require transformations to fit in an ecosystem. In this paper, we discuss several integration problems in the field of Low Power Wide Area Networks in the context of the Port of the Future and propose a new distributed platform architecture, called FLINT. FLINT is a framework to program flexible and configurable flows on a per device basis. A flow is constructed from fine-grained components, called adapters. Due to the modularity of an adapter, users can easily integrate existing software. We evaluated FLINT based on five levels of interoperability and show that FLINT can be used to interconnect non-interoperable systems and protocols on every level. We have also implemented FLINT in a container based environment and demonstrated that a basic configuration has a 99% forwarding rate of 17.500 513-byte packets per second, showing that the architecture can deliver good performance

FLINT : flows for the Internet of Things

New protocols and technologies are continuously competing in the Internet of Things. This has resulted in a fragmented landscape that complicates the integration of different solutions. Standardization efforts try to avoid this problem, however within a certain ecosystem, multiple standards still require integration to enable trans-sector innovation. Moreover, existing devices require transformations to fit in an ecosystem. In this paper, we discuss several integration problems in the field of Low Power Wide Area Networks in the context of the Port of the Future and propose a new distributed platform architecture, called FLINT. FLINT is a framework to program flexible and configurable flows on a per device basis. A flow is constructed from fine-grained components, called adapters. Due to the modularity of an adapter, users can easily integrate existing software. We evaluated FLINT based on five levels of interoperability and show that FLINT can be used to interconnect non-interoperable systems and protocols on every level. We have also implemented FLINT in a container based environment and demonstrated that a basic configuration has a 99% forwarding rate of 17.500 513-byte packets per second, showing that the architecture can deliver good performance

Cancer screening participation and gender stratification in Europe

The current study examines whether the extent of macrolevel gender inequality affects the association between women’s educational attainment and their participation in cervical and breast cancer screening and how this relationship is moderated by a country’s cancer screening strategy (organized vs. opportunistic). A multilevel design with women (Ncervical = 99,794; Nbreast = 55,021) nested in 30 European countries was used to analyze data from the European Health Interview Survey (2013–2015). Results of multilevel logistic regression models demonstrate that higher macrolevel gender inequality is associated with (a) a lower overall likelihood that women have had a mammography and Pap smear and (b) a larger gap in participation between women with low and high levels of education, regardless of a country’s screening strategy (i.e., no moderation by a country’s screening strategy was found). We conclude that macrolevel gender stratification should not be neglected when designing cancer screening policy

Cervical cancer (over)screening in Belgium and Switzerland: trends and social inequalities

Cervical cancer screening (CCS) by means of Pap smears has led to a decrease in cervical cancer incidence and mortality. In the absence of organized programmes, CCS is opportunistic in Belgium and Switzerland. This might result in a high level of CCS overuse, as screening practices do not conform to the recommended 3-yearly screening interval and the target age-ranges (Belgium: 25–64, Switzerland: 20–70). This study aimed to assess trends in CCS uptake and overuse in Belgium and Switzerland and their social determinants, in the light of reimbursement initiatives, which were implemented in both countries.Methods: Data from five waves of the Belgian Health Interview Survey (1997–2013) (N=11 141) and Swiss Health Interview Survey (1992–2012) (N=32 696) were used. We performed Poisson regressions to estimate adjusted prevalence ratios (APR), controlled for socio-economic and socio- demographic characteristics and health status. CCS overuse was operationalized as screening more than once every 3 years and screening above recommended age- range.Results: CCS uptake remained relatively stable over time, with a mean coverage of 70.9% in Belgium and 73.1% in Switzerland. Educational and income gradients were found in both countries. Concerning CCS overuse, women above screening-eligible age showed consistently high screening rates, but screening within the past year declined significantly in both countries, matching the temporal implementation of the reimbursement initiatives.ConclusionsAlthough no increase in CCS coverage could be established, CCS has become more efficient in both countries as Pap smear overuse at the population level has declined after the implementation of reimbursement measures tackling CCS overuse