Autonomous planning tool for changeable assembly systems

Car manufacturers are expected to start series production of fuel cell vehicles within the next years. Simultaneously, other industries are pushing towards the utilization of fuel cells. Fuel cell manufacturers need to scale up production at the right time and react to changing product requirements with the ideal level and point of changeability. This complex task requires methods and tools for decision support. The authors present SkaliA, an autonomous planning tool, which generates guidelines for the efficient use of change enablers specific to an assembly system. The planning tool is demonstrated on the example of an assembly system for high pressure valves used in fuel cell applications

Pion-nucleus optical potential valid up to the DELTA-resonance region

We present in this article an optical potential for the $\pi$-nucleus interaction that can be used in various studies involving $\pi$-nucleus channels. Based on earlier treatments of the low energy $\pi$-nucleus optical potential, we have derived a potential expression applicable from threshold up to the $\Delta$-resonance region. We extracted the impulse approximation form for this potential from the $\pi-N$ scattering amplitude and then added to it kinematical and physical corrections. The kinematic corrections arise from transforming the impulse approximation expression from the $\pi-N$ center of mass frame to the $\pi$-nucleus center of mass frame, while the physical corrections arise mostly from the many-body nature of the $\pi$-nucleus interaction. By taking advantage of the experimental progress in our knowledge of the $\pi-N$ process, we have updated earlier treatments with parameters calculated from state-of-the-art experimental measurements.Comment: 23 pages, 12 figures. Accepted for publication in Physical Review

Beta(2)-adrenergic receptor (ADRB2) gene polymorphisms and risk of COPD exacerbations : the Rotterdam study

The role of the beta(2)-adrenergic receptor (ADRB2) gene in patients with chronic obstructive pulmonary disease (COPD) is unclear. We investigated the association between ADRB2 variants and the risk of exacerbations in COPD patients treated with inhaled beta(2)-agonists. Within the Rotterdam Study, a population-based cohort study, we followed 1053 COPD patients until the first COPD exacerbation or end of follow-up and extracted rs1042713 (16Arg > Gly) and rs1042714 (27Gln > Glu) in ADRB2. Exposure to inhaled beta(2)-agonists was categorized into current, past, or non-use on the index date (date of COPD exacerbation for cases and on the same day of follow-up for controls). COPD exacerbations were defined as acute episodes of worsening symptoms requiring systemic corticosteroids and/or antibiotics (moderate exacerbations), or hospitalization (severe exacerbations). The associations between ADRB2 variants and COPD exacerbations were assessed using Cox proportional hazards models, adjusting for age, sex, use of inhaled corticosteroids, daily dose of beta(2)-agonists, and smoking. In current users of beta(2)-agonists, the risk of COPD exacerbation decreased by 30% (hazard ratio (HR); 0.70, 95% CI: 0.59-0.84) for each copy of the Arg allele of rs1042713 and by 20% (HR; 0.80, 95% CI: 0.69-0.94) for each copy of the Gln allele of rs1042714. Furthermore, current users carrying the Arg16/Gln27 haplotype had a significantly lower risk (HR; 0.70, 95% CI: 0.59-0.85) of COPD exacerbation compared to the Gly16/Glu27 haplotype. In conclusion, we observed that the Arg16/Gln27 haplotype in ADRB2 was associated with a reduced risk of COPD exacerbation in current users of inhaled beta(2)-agonists

Designing an adaptive production control system using reinforcement learning

Modern production systems face enormous challenges due to rising customer requirements resulting in complex production systems. The operational efficiency in the competitive industry is ensured by an adequate production control system that manages all operations in order to optimize key performance indicators. Currently, control systems are mostly based on static and model-based heuristics, requiring significant human domain knowledge and, hence, do not match the dynamic environment of manufacturing companies. Data-driven reinforcement learning (RL) showed compelling results in applications such as board and computer games as well as first production applications. This paper addresses the design of RL to create an adaptive production control system by the real-world example of order dispatching in a complex job shop. As RL algorithms are “black box” approaches, they inherently prohibit a comprehensive understanding. Furthermore, the experience with advanced RL algorithms is still limited to single successful applications, which limits the transferability of results. In this paper, we examine the performance of the state, action, and reward function RL design. When analyzing the results, we identify robust RL designs. This makes RL an advantageous control system for highly dynamic and complex production systems, mainly when domain knowledge is limited

Hybrid sideways/longitudinal swimming in the monoflagellate Shewanella oneidensis: from aerotactic band to biofilm

Shewanella oneidensis MR-1 are facultative aerobic electroactive bacteria, with an appealing potential for sustainable energy production and bioremediation. They gather around air sources, forming aerotactic bands and biofilms. Though accumulation is crucial to technological exploitation, their collective behaviour remains poorly reported. Here we establish a comprehensive framework for the study of aerotaxis, unveiling a novel hybrid locomotion pattern. Despite having only one flagellum, MR-1 combine motility features of mono- and multiflagellate bacteria, alternating longitudinal fast and sideways slow swimming. The adaptive tuning of the resulting bimodal velocity distributions fulfils different biological functions, such as aerotaxis and confinement. Overall, we reveal the mechanisms underlying the aerotactic collective behaviour of MR-1, in the process leading from accumulation to biofilm formatio

Augmented Go & See: An approach for improved bottleneck identification in production lines

Bottlenecks in production lines are often shifting and thus hard to identify. They lead to decreased output, longer throughput times and higher work in progress. Go & See is a well-established Lean practice where managers go to the shop floor to see the problems first hand. Mixed reality is a promising technology to improve transparency in complex production environments. Until recently, mixed reality applications have been very demanding in terms of computing power requiring high performance hardware. This paper presents an approach for real-time KPI visualization using mixed reality for bottleneck identification in production lines relying on the bring-your-own device principle. The developed application uses image recognition to identify work stations and visualizes cycle times and work in progress in augmented reality. With this additional information, it is possible to discern different root causes for bottlenecks, for example systematically higher or varying cycle times due to breakdowns. This solution can be classified according to the acatech industry 4.0 maturity model as a level 3 - transparency - application. It could be shown that the identification of bottlenecks and underlying reasons has been improved compared to standard Go & See

Individual dosage of digoxin in patients with heart failure

Backgroud: After the publication of DIG trial, the therapeutic target of serum digoxin concentration (SDC) for the treatment of heart failure (HF) has been lowered (0.40-1.00 ng/ml). However, the majority of equations to calculate digoxin dosages were developed for higher SDCs. Recently, a new equation was validated in Asian population for low SDCs by Konishi et al., but results in Caucasians are unknown. Aim: This study was aimed to test the Konishi equation in Caucasians specifically targeting low SDCs. Furthermore, the Konishi equation was compared with other frequently used equations. Design: This was a prospective, multicenter study. Methods: Clinically indicated digoxin was given in 40 HF patients. The dosage was calculated with the Konishi equation. The SDC was measured at 1 and 6 months after starting digoxin. Adherence to digoxin was monitored with a specific questionnaire. Results: After exclusion of patients admitting poor adherence, we found a reasonable correlation between predicted and measured SDC (r = 0.48; P < 0.01) by the Konishi equation. Excluding patients with poor adherence and relevant worsening of renal function, the measured SDC (n = 54 measurements) was within the pre-defined therapeutic range in 95% of the cases. The mean, maximal and minimal measured SDC were 0.69 ± 0.19, 1.00 and 0.32 ng/ml, respectively. The correlation was weaker for the Jelliffe, the Koup and Jusko, and the Bauman equations. Conclusions: This study supports the clinical validity of the Konishi equation for calculating individual digoxin dosage in Caucasians, targeting SDCs according to current HF guideline

Spironolactone and risk of upper gastrointestinal events: population based case-control study

OBJECTIVE: To confirm and quantify any association between spironolactone and upper gastrointestinal bleeding and ulcers. DESIGN: Population based case-control study. SETTING: A primary care information database in the Netherlands. PARTICIPANTS: All people on the database who were aged 18 or more between 1 January 1996 and 30 September 2003. Patients with a history of alcoholism or gastrointestinal cancer were excluded. Ten controls were matched to each case of gastroduodenal ulcer or upper gastrointestinal bleeding by age (year of birth), sex, and index date. MAIN OUTCOME MEASURES: The occurrence of an upper gastrointestinal event (bleeding or ulcers), adjusted for potential confounders with conditional logistic regression analysis. RESULTS: Within the source population of 306 645 patients, 523 cases of gastric or duodenal ulcer or upper gastrointestinal

Bone mineral density and chronic lung disease mortality: the Rotterdam study

Context: Low bone mineral density (BMD) has been associated with increased all-cause mortality. Cause-specific mortality studies have been controversial. Objective: The aim of the study was to investigate associations between BMD and all-cause mortality and in-depth cause-specific mortality. Design and Setting: We studied two cohorts from the prospective Rotterdam Study (RS), initiated in 1990 (RS-I) and 2000 (RS-II) with average follow-up of 17.1 (RS-I) and 10.2 (RS-II) years until January 2011. Baseline femoral neck BMD was analyzed in SD values. Deaths were classified according to International Classification of Diseases into seven groups: cardiovascular diseases, cancer, infections, external, dementia, chronic lung diseases, and other causes. Gender-stratified Cox and competing-risks models were adjusted for age, body mass index, and smoking. Participants: The study included 5779 subjects from RS-I and 2055 from RS-II. Main Outcome Measurements: We measured all-cause and cause-specific mortality. Results: A significant inverse association between BMD and all-cause mortality was found in males [expressed as hazard ratio (95% confidence interval)]: RS-I, 1.07 (1.01-1.13), P = .020; RS-II, 1.31 (1.12-1.55), P = .001); but it was not found in females: RS-I, 1.05 (0.99-1.11), P = .098; RS-II, 0.91 (0.74-1.12), P = .362. An inverse association with chronic lung disease mortality was found in males [RS-I, 1.75 (1.34-2.29), P < .001; RS-II, 2.15 (1.05-4.42), P = .037] and in RS-I in females [1.72 (1.16-2.57); P = .008], persisting after multiple adjustments and excluding prevalent chronic obstructive pulmonary disease. A positive association between BMD and cancer mortality was detected in females in RS-I [0.89 (0.80-0.99); P = .043]. No association was found with cardiovascular mortality. Conclusions: BMD is inversely associated with mortality. The strong association of BMD with chronic lung disease mortality is a novel finding that needs further analysis to clarify underlying mechanisms