Visual analysis for spatio-temporal event correlation in manufacturing

The analysis of events with spatio-temporal context and their interdependencies is a crucial task in the manufacturing domain. In general, understanding this context, for example investigating error messages or alerts is important to take corrective actions. In the manufacturing domain, comprehending the relations of errors is often based on the technicians\u27 experience. Validation of cause-effect relations is necessary to understand if an effect has a preceding causality, e.g., if an error is the result of multiple issues from previous working steps. We present an approach to investigate spatio-temporal relations between such events. Based on a time-sensitive correlation measure, we provide multiple coordinated views to analyze and filter the data. In collaboration with an industry partner, we developed a visual analytics approach for error logs reported by machines that covers a multitude of analysis tasks. We present a case study based on real-world event logs of an assembly line with feedback from our industry partner\u27s domain experts. The findings show that experts can effectively identify error dependencies that impair the overall assembly line productivity using our technique. Furthermore, we discuss how our approach is applicable in other domains

BlueCollar: Optimizing Worker Paths on Factory Shop Floors with Visual Analytics

The optimization of a factory\u27s productivity regarding quality and efficiency is an important task in the manufacturing domain. To optimize the productivity, production lines are optimized to have short transportation paths and short processing times at the stations that process intermediate components or the final product. A factory\u27s layout is a key factor in this optimization aspect. This optimization mostly comprises the machine tools\u27 positions with respect to places where supply goods are being delivered and other tools are stationed, often neglecting the paths that workers need to take at the shop floor. This impairs a factory\u27s productivity, as machines may need to wait for workers, who operated another machine and are still on the way due to the long distance between the machines. In this work, we present BlueCollar, a visual analytics approach that supports layout planners to explore and optimize existing factory layouts regarding the paths taken by workers. Planners can visually inspect the paths that workers need to take based on their work schedule and the factory\u27s layout. An estimation of distribution algorithm supports them in choosing which layout elements, e.g., shared tool caches, to relocate. Its intermediate and final results are used to provide visual cues for suitable relocation areas, and to suggest new layouts automatically. We demonstrate our approach through an application scenario based on a realistic prototype layout provided by an external company

Beta defensin-2 is reduced in central but not in distal airways of smoker COPD patients

Background: Altered pulmonary defenses in chronic obstructive pulmonary disease (COPD) may promote distal airways bacterial colonization. The expression/activation of Toll Like receptors (TLR) and beta 2 defensin (HBD2) release by epithelial cells crucially affect pulmonary defence mechanisms. Methods: The epithelial expression of TLR4 and of HBD2 was assessed in surgical specimens from current smokers COPD (s-COPD; n = 17), ex-smokers COPD (ex-s-COPD; n = 8), smokers without COPD (S; n = 12), and from non-smoker non-COPD subjects (C; n = 13). Results: In distal airways, s-COPD highly expressed TLR4 and HBD2. In central airways, S and s-COPD showed increased TLR4 expression. Lower HBD2 expression was observed in central airways of s-COPD when compared to S and to ex-s-COPD. s-COPD had a reduced HBD2 gene expression as demonstrated by real-time PCR on micro-dissected bronchial epithelial cells. Furthermore, HBD2 expression positively correlated with FEV1/FVC ratio and inversely correlated with the cigarette smoke exposure. In a bronchial epithelial cell line (16 HBE) IL-1β significantly induced the HBD2 mRNA expression and cigarette smoke extracts significantly counteracted this IL-1 mediated effect reducing both the activation of NFkB pathway and the interaction between NFkB and HBD2 promoter. Conclusions: This study provides new insights on the possible mechanisms involved in the alteration of innate immunity mechanisms in COPD. © 2012 Pace et al

Exposure to Moderate Air Pollution during Late Pregnancy and Cord Blood Cytokine Secretion in Healthy Neonates

Ambient air pollution can alter cytokine concentrations as shown in vitro and following short-term exposure to high air pollution levels in vivo. Exposure to pollution during late pregnancy has been shown to affect fetal lymphocytic immunophenotypes. However, effects of prenatal exposure to moderate levels of air pollutants on cytokine regulation in cord blood of healthy infants are unknown. In a birth cohort of 265 healthy term-born neonates, we assessed maternal exposure to particles with an aerodynamic diameter of 10 µm or less (PM₁₀), as well as to indoor air pollution during the last trimester, specifically the last 21, 14, 7, 3 and 1 days of pregnancy. As a proxy for traffic-related air pollution, we determined the distance of mothers' homes to major roads. We measured cytokine and chemokine levels (MCP-1, IL-6, IL-10, IL-1ß, TNF-α and GM-CSF) in cord blood serum using LUMINEX technology. Their association with pollution levels was assessed using regression analysis, adjusted for possible confounders. Mean (95%-CI) PM₁₀ exposure for the last 7 days of pregnancy was 18.3 (10.3-38.4 µg/m³). PM₁₀ exposure during the last 3 days of pregnancy was significantly associated with reduced IL-10 and during the last 3 months of pregnancy with increased IL-1ß levels in cord blood after adjustment for relevant confounders. Maternal smoking was associated with reduced IL-6 levels. For the other cytokines no association was found. Our results suggest that even naturally occurring prenatal exposure to moderate amounts of indoor and outdoor air pollution may lead to changes in cord blood cytokine levels in a population based cohort

Neurologic complications in patients receiving aortic versus subclavian versus femoral arterial cannulation for post-cardiotomy extracorporeal life support:results of the PELS observational multicenter study

BACKGROUND: Cerebral perfusion may change depending on arterial cannulation site and may affect the incidence of neurologic adverse events in post-cardiotomy extracorporeal life support (ECLS). The current study compares patients' neurologic outcomes with three commonly used arterial cannulation strategies (aortic vs. subclavian/axillary vs. femoral artery) to evaluate if each ECLS configuration is associated with different rates of neurologic complications. METHODS: This retrospective, multicenter (34 centers), observational study included adults requiring post-cardiotomy ECLS between January 2000 and December 2020 present in the Post-Cardiotomy Extracorporeal Life Support (PELS) Study database. Patients with Aortic, Subclavian/Axillary and Femoral cannulation were compared on the incidence of a composite neurological end-point (ischemic stroke, cerebral hemorrhage, brain edema). Secondary outcomes were overall in-hospital mortality, neurologic complications as cause of in-hospital death, and post-operative minor neurologic complications (seizures). Association between cannulation and neurological outcomes were investigated through linear mixed-effects models. RESULTS: This study included 1897 patients comprising 26.5% Aortic (n = 503), 20.9% Subclavian/Axillary (n = 397) and 52.6% Femoral (n = 997) cannulations. The Subclavian/Axillary group featured a more frequent history of hypertension, smoking, diabetes, previous myocardial infarction, dialysis, peripheral artery disease and previous stroke. Neuro-monitoring was used infrequently in all groups. Major neurologic complications were more frequent in Subclavian/Axillary (Aortic: n = 79, 15.8%; Subclavian/Axillary: n = 78, 19.6%; Femoral: n = 118, 11.9%; p &lt; 0.001) also after mixed-effects model adjustment (OR 1.53 [95% CI 1.02-2.31], p = 0.041). Seizures were more common in Subclavian/Axillary (n = 13, 3.4%) than Aortic (n = 9, 1.8%) and Femoral cannulation (n = 12, 1.3%, p = 0.036). In-hospital mortality was higher after Aortic cannulation (Aortic: n = 344, 68.4%, Subclavian/Axillary: n = 223, 56.2%, Femoral: n = 587, 58.9%, p &lt; 0.001), as shown by Kaplan-Meier curves. Anyhow, neurologic cause of death (Aortic: n = 12, 3.9%, Subclavian/Axillary: n = 14, 6.6%, Femoral: n = 28, 5.0%, p = 0.433) was similar. CONCLUSIONS:In this analysis of the PELS Study, Subclavian/Axillary cannulation was associated with higher rates of major neurologic complications and seizures. In-hospital mortality was higher after Aortic cannulation, despite no significant differences in incidence of neurological cause of death in these patients. These results encourage vigilance for neurologic complications and neuromonitoring use in patients on ECLS, especially with Subclavian/Axillary cannulation.</p

Characteristics and Outcomes of Prolonged Venoarterial Extracorporeal Membrane Oxygenation after Cardiac Surgery:The Post-Cardiotomy Extracorporeal Life Support (PELS-1) Cohort Study

OBJECTIVES: Most post-cardiotomy (PC) extracorporeal membrane oxygenation (ECMO) runs last less than 7 days. Studies on the outcomes of longer runs have provided conflicting results. This study investigates patient characteristics and short- and long-term outcomes in relation to PC ECMO duration, with a focus on prolonged (&gt; 7 d) ECMO. DESIGN: Retrospective observational cohort study. SETTING: Thirty-four centers from 16 countries between January 2000 and December 2020. PATIENTS: Adults requiring post PC ECMO between 2000 and 2020. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Characteristics, in-hospital, and post-discharge outcomes were compared among patients categorized by ECMO duration. Survivors and nonsurvivors were compared in the subgroup of patients with ECMO duration greater than 7 days. The primary outcome was in-hospital mortality. Two thousand twenty-one patients were included who required PC ECMO for 0-3 days (n = 649 [32.1%]), 4-7 days (n = 776 [38.3%]), 8-10 days (n = 263 [13.0%]), and greater than 10 days (n = 333 [16.5%]). There were no major differences in the investigated preoperative and procedural characteristics among ECMO duration groups. However, the longer ECMO duration category was associated with multiple complications including bleeding, acute kidney injury, arrhythmias, and sepsis. Hospital mortality followed a U-shape curve, with lowest mortality in patients with ECMO duration of 4-7 days (n = 394, 50.8%) and highest in patients with greater than 10 days ECMO support (n = 242, 72.7%). There was no significant difference in post-discharge survival between ECMO duration groups. In patients with ECMO duration greater than 7 days, age, comorbidities, valvular diseases, and complex procedures were associated with nonsurvival. CONCLUSIONS: Nearly 30% of PC ECMO patients were supported for greater than 7 days. In-hospital mortality increased after 7 days of support, especially in patients undergoing valvular and complex surgery, or who had complications, although the long-term post-discharge prognosis was comparable to PC ECMO patients with shorter support duration.</p

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Spatio-temporal and immersive visual analytics for advanced manufacturing

The increasing amount of digitally available information in the manufacturing domain is accompanied by a demand to use these data to increase the efficiency of a product’s overall design, production, and maintenance steps. This idea, often understood as a part of Industry 4.0, requires the integration of information technologies into traditional manufacturing craftsmanship. Despite an increasing amount of automation in the production domain, human creativity is still essential when designing new products. Further, the cognitive ability of skilled workers to comprehend complex situations and solve issues by adapting solutions of similar problems makes them indispensable. Nowadays, customers demand highly customizable products. Therefore, modern factories need to be highly flexible regarding the lot size and adaptable regarding the produced goods, resulting in increasingly complex processes. One of the major challenges in the manufacturing domain is to optimize the interplay of human expert knowledge and experience with data analysis algorithms. Human experts can quickly comprehend previously unknown patterns and transfer their knowledge and gained experience to solve new issues. Contrarily, data analysis algorithms can process tasks very efficiently at the cost of limited adaptability to handle new situations. Further, they usually lack a sense of semantics, which leads to a need to combine them with human world knowledge to assess the meaningfulness of such algorithms’ results. The concept of Visual Analytics combines the advantages of the human’s cognitive abilities and the processing power of computers. The data are visualized, allowing the users to understand and manipulate them interactively, while algorithms process the data according to the users’ interaction. In the manufacturing domain, a common way to describe the different states of a product from the idea throughout the realization until the product is disposed is the product lifecycle. This thesis presents approaches along the first three phases of the lifecycle: design, planning, and production. A challenge that all of the phases face is that it is necessary to be able to find, understand, and assess relations, for example between concepts, production line layouts, or events reported in a production line. As all phases of the product lifecycle cover broad topics, this thesis focuses on supporting experts in understanding and comparing relations between important aspects of the respective phases, such as concept relationships in the patent domain, as well as production line layouts, or relations of events reported in a production line. During the design phase, it is important to understand the relations of concepts, such as key concepts in patents. Hence, this thesis presents approaches that help domain experts to explore the relationship of such concepts visually. It first focuses on the support of analyzing patent relationships and then extends the presented approach to convey relations about arbitrary concepts, such as authors in scientific literature or keywords on websites. During the planning phase, it is important to discover and compare different possibilities to arrange production line components and additional stashes. In this field, the digitally available data is often insufficient to propose optimal layouts. Therefore, this thesis proposes approaches that help planning experts to design new layouts and optimize positions of machine tools and other components in existing production lines. In the production phase, supporting domain experts in understanding recurring issues and their relation is important to improve the overall efficiency of a production line. This thesis presents visual analytics approaches to help domain experts to understand the relation between events reported by machine tools and comprehend recurring error patterns that may indicate systematic issues during production. Then, this thesis combines the insights and lessons learned from the previous approaches to propose a system that combines augmented reality with visual analysis to allow the monitoring and a situated analysis of machine events directly at the production line. The presented approach primarily focuses on the support of operators on the shop floor. At last, this thesis discusses a possible combination of the product lifecycle with knowledge generating models to communicate insights between the phases, e.g., to prevent issues that are caused from problematic design decisions in earlier phases. In summary, this thesis makes several fundamental contributions to advancing visual analytics techniques in the manufacturing domain by devising new interactive analysis techniques for concept and event relations and by combining them with augmented reality approaches enabling an immersive analysis to improve event handling during production

Platform workers centre stage! Taking stock of current debates and approaches for improving the conditions of platform work in Europe

A growing body of literature seeks to understand the conditions and consequences of platform work for platform workers and society at large. This study takes stock of current literature on platform work in Europe, discerns central debates (terms and definitions, relevance and diffusion, worker motivations and working conditions) and synthesizes knowledge on approaches for improving platform worker's conditions at different levels (worker, platform and regulatory level)