Using Neural Networks by Modelling Semi-Active Shock Absorber

A permanently increasing number of on-board automotive control systems requires new approaches to their digital mapping that improves functionality in terms of adaptability and robustness as well as enables their easier on-line software update. As it can be concluded from many recent studies, various methods applying neural networks (NN) can be good candidates for relevant digital twin (DT) tools in automotive control system design, for example, for controller parameterization and condition monitoring. However, the NN-based DT has strong requirements to an adequate amount of data to be used in training and design. In this regard, the paper presents an approach, which demonstrates how the regression tasks can be efficiently handled by the modeling of a semi-active shock absorber within the DT framework. The approach is based on the adaptation of time series augmentation techniques to the stationary data that increases the variance of the latter. Such a solution gives a background to elaborate further data engineering methods for the data preparation of sophisticated databases

Datenbasierte Simulationsumgebung für das Training autonomer, maschineller Regelungssysteme

Nach der Auslegung und Produktion komplexer Systeme, folgen oft umfangreiche Tests zum Nachweis der Produktfähigkeit über die Grenzen der vorausgelegten Randbedingungen hinweg. Solche Tests erfolgen häufig automatisiert unter bestmöglicher Reproduktion der späteren Einsatzbedingungen. Die dabei gemessenen Daten spiegeln das Systemverhalten in Form von Mess-, Berechnungs- und Stellgrößen wieder. Mithilfe dieser Daten soll in der vorliegenden Arbeit ein Vorgehen beschrieben werden, dass sie nutzt und durch den Einsatz neuronaler Netze in eine Black-Box Simulationsumgebung überführt. Diese Simulationsumgebung wird dann dazu verwendet, dass Systemverhalten vorherzusagen, Abweichungen zu erkennen und vor allem autonome Lernalgorithmen auf das System anzuwenden, denn selbst wenn das System fertig entwickelt ist, so bedarf es oft immer noch einer manuellen Parametrisierung der Systemsteuerung

A survey on engineering approaches for self-adaptive systems (extended version)

The complexity of information systems is increasing in recent years, leading to increased effort for maintenance and configuration. Self-adaptive systems (SASs) address this issue. Due to new computing trends, such as pervasive computing, miniaturization of IT leads to mobile devices with the emerging need for context adaptation. Therefore, it is beneficial that devices are able to adapt context. Hence, we propose to extend the definition of SASs and include context adaptation. This paper presents a taxonomy of self-adaptation and a survey on engineering SASs. Based on the taxonomy and the survey, we motivate a new perspective on SAS including context adaptation

Acute myocardial infarction occurring in versus out of the hospital: patient characteristics and clinical outcome

AbstractOBJECTIVESWe describe the baseline characteristics and clinical course of patients who had an acute myocardial infarction (AMI) during their hospital stay.BACKGROUNDIn comparison with patients who had an AMI outside of the hospital (prehospital AMI), the data on patients who had an AMI in the hospital are poorly described.METHODSPatients with an in-hospital AMI were prospectively registered in the Southwest German Maximal Individual TheRapy in Acute myocardial infarction (MITRA) study and compared with patients with prehospital AMI.RESULTSOf 5,888 patients with AMI, 403 patients (6.8%) had an in-hospital AMI. These patients were older, more often male and sicker as compared with the patients with a prehospital AMI. They also showed a higher prevalence of concomitant diseases, such as arterial hypertension, diabetes mellitus, renal insufficiency and contraindications for thrombolysis. There was no significant difference regarding the use of reperfusion therapy, either thrombolysis (in-hospital AMI 44.2% vs. prehospital AMI 49.1%; odds ratio [OR] 0.86, 95% confidence interval [CI] 0.70 to 1.05) or primary angioplasty (9.9% vs. 8.2%; OR 1.23, 95% CI 0.88 to 1.73), or a combination of both, between the two groups. The interval from symptom onset to the start of treatment in patients receiving reperfusion therapy was 55 min for patients with an in-hospital AMI versus 180 min for patients with a prehospital AMI (p = 0.001). In-hospital death occurred in 110 (27.3%) of 403 patients with an in-hospital versus 762 (13.9%) of 5,485 patients with a prehospital AMI (OR 2.33, 95% CI 1.85 to 2.94). This was confirmed by logistic regression analysis after adjusting for other confounding variables (OR 1.67, 95% CI 1.23 to 2.24).CONCLUSIONSIn-hospital AMI occurred in 6.8% of patients. Time to intervention was shorter; however, the use of reperfusion therapy for in-hospital AMI was not different from that for prehospital AMI. In particular, primary angioplasty seems to be underused in these patients. This, as well as the selection of patients, may result in the high hospital mortality rate of 27.3%

Interventions to reduce stress and prevent burnout in healthcare professionals supported by digital applications: a scoping review

Aim: Healthcare professionals are at increased risk of burnout, primarily due to workplace-related stressors. The COVID-19 pandemic has further increased this risk. Different interventions exist with varying degrees of effectiveness; little is reported on the content and implementation of such programs. This review fills this gap, with attention to recent programs using digital components. Methods: PubMed, Embase, PsycInfo, and Google Scholar were searched between January 24th and 28th, 2022, limited to the last 5 years (≥2017). Articles were included if they (1) focused on stress reduction or burnout prevention for nurses and medical doctors within workplace health promotion for nurses or medical doctors, (2) included a digital program component, (3) were conducted in high-income country contexts, and (4) were clinical studies published in English or German. Data was extracted using a priori designed spreadsheets. A group of at least 2 authors at each stage carried out the screening, selection, and data extraction. Results: The search strategy identified 153 articles, all except 7 were excluded. Two studies were conducted in the USA, two in Spain, one in the Netherlands, Poland, and Korea each. Four studies used a randomized study design, all but one had a control group. A wide range of outcome measures was used. The types of interventions included an adapted mindfulness-based stress reduction program combined with aspects of behavioral therapies, cognitive behavioral therapy, or acceptance and commitment therapy. The digital components used were apps (4 studies), a digital platform, blended learning, and a web-based intervention (1 study each). Six studies focused on individual interventions, one included organizational interventions. Conclusion: Despite an acute burnout crisis in the healthcare sector, only seven recent interventions were found that integrated digital components. Several problems emerged during the implementation of the interventions that made it clear that organizational support is urgently needed for successful implementation. Although interventions for stress reduction and burnout prevention should combine individual and organizational measures to be as successful as possible, this was only partially the case in one of the intervention programs. The results of this scoping review can be used to further develop or optimize stress and burnout prevention programs

Stroma AReactive Invasion Front Areas (SARIFA) - a new easily to determine biomarker in Colon cancer - results of a retrospective study

Simple Summary Many studies have used histomorphological features to more precisely predict the prognosis of patients with colon cancer, focusing on tumor budding, poorly differentiated clusters, and the tumor–stroma ratio. Here, we introduce SARIFA: Stroma AReactive Invasion Front Area(s). We defined SARIFA as the direct contact between a tumor gland/tumor cell cluster (≥5 cells) and inconspicuous surrounding adipose tissue in the invasion front. SARIFA shows an excellent interobserver reliability and high prognostic value and is thus a promising histomorphological prognostic indicator for adipose-infiltrative adenocarcinomas of the colon. Abstract Many studies have used histomorphological features to more precisely predict the prognosis of patients with colon cancer, focusing on tumor budding, poorly differentiated clusters, and the tumor–stroma ratio. Here, we introduce SARIFA: Stroma AReactive Invasion Front Area(s). We defined SARIFA as the direct contact between a tumor gland/tumor cell cluster (≥5 cells) and inconspicuous surrounding adipose tissue in the invasion front. In this retrospective, single-center study, we classified 449 adipose-infiltrative adenocarcinomas (not otherwise specified) from two groups based on SARIFA and found 25% of all tumors to be SARIFA-positive. Kappa values between the two pathologists were good/very good: 0.77 and 0.87. Patients with SARIFA-positive tumors had a significantly shorter colon-cancer-specific survival (p = 0.008, group A), absence of metastasis, and overall survival (p < 0.001, p = 0.003, group B). SARIFA was significantly associated with adverse features such as pT4 stage, lymph node metastasis, tumor budding, and higher tumor grade. Moreover, SARIFA was confirmed as an independent prognostic indicator for colon-cancer-specific survival (p = 0.011, group A). SARIFA assessment was very quick (<1 min). Because of low interobserver variability and good prognostic significance, SARIFA seems to be a promising histomorphological prognostic indicator in adipose-infiltrative adenocarcinomas of the colon. Further studies should validate our results and also determine whether SARIFA is a universal prognostic indicator in solid cancers