Process-Driven and Flow-Based Processing of Industrial Sensor Data.

For machine manufacturing companies, besides the production of high quality and reliable machines, requirements have emerged to maintain machine-related aspects through digital services. The development of such services in the field of the Industrial Internet of Things (IIoT) is dealing with solutions such as effective condition monitoring and predictive maintenance. However, appropriate data sources are needed on which digital services can be technically based. As many powerful and cheap sensors have been introduced over the last years, their integration into complex machines is promising for developing digital services for various scenarios. It is apparent that for components handling recorded data of these sensors they must usually deal with large amounts of data. In particular, the labeling of raw sensor data must be furthered by a technical solution. To deal with these data handling challenges in a generic way, a sensor processing pipeline (SPP) was developed, which provides effective methods to capture, process, store, and visualize raw sensor data based on a processing chain. Based on the example of a machine manufacturing company, the SPP approach is presented in this work. For the company involved, the approach has revealed promising results.

Anomaly Detections for Manufacturing Systems Based on Sensor Data-Insights into Two Challenging Real-World Production Settings.

To build, run, and maintain reliable manufacturing machines, the condition of their components has to be continuously monitored. When following a fine-grained monitoring of these machines, challenges emerge pertaining to the (1) feeding procedure of large amounts of sensor data to downstream processing components and the (2) meaningful analysis of the produced data. Regarding the latter aspect, manifold purposes are addressed by practitioners and researchers. Two analyses of real-world datasets that were generated in production settings are discussed in this paper. More specifically, the analyses had the goals (1) to detect sensor data anomalies for further analyses of a pharma packaging scenario and (2) to predict unfavorable temperature values of a 3D printing machine environment. Based on the results of the analyses, it will be shown that a proper management of machines and their components in industrial manufacturing environments can be efficiently supported by the detection of anomalies. The latter shall help to support the technical evangelists of the production companies more properly.

Dimensionality Reduction and Subspace Clustering in Mixed Reality for Condition Monitoring of High-Dimensional Production Data.

Visual analytics are becoming increasingly important in the light of big data and related scenarios. Along this trend, the field of immersive analytics has been variously furthered as it is able to provide sophisticated visual data analytics on one hand, while preserving user-friendliness on the other. Furthermore, recent hardware developments such as smart glasses, as well as achievements in virtual-reality applications, have fanned immersive analytic solutions. Notably, such solutions can be very effective when they are applied to high-dimensional datasets. Taking this advantage into account, the work at hand applies immersive analytics to a high-dimensional production dataset to improve the digital support of daily work tasks. More specifically, a mixed-reality implementation is presented that will support manufacturers as well as data scientists to comprehensively analyze machine data. As a particular goal, the prototype will simplify the analysis of manufacturing data through the usage of dimensionality reduction effects. Therefore, five aspects are mainly reported in this paper. First, it is shown how dimensionality reduction effects can be represented by clusters. Second, it is presented how the resulting information loss of the reduction is addressed. Third, the graphical interface of the developed prototype is illustrated as it provides (1) a correlation coefficient graph, (2) a plot for the information loss, and (3) a 3D particle system. In addition, an implemented voice recognition feature of the prototype is shown, which was considered to be being promising to select or deselect data variables users are interested in when analyzing the data. Fourth, based on a machine learning library, it is shown how the prototype reduces computational resources using smart glasses. The main idea is based on a recommendation approach as well as the use of subspace clustering. Fifth, results from a practical setting are presented, in which the prototype was shown to domain experts. The latter reported that such a tool is actually helpful to analyze machine data daily. Moreover, it was reported that such a system can be used to educate machine operators more properly. As a general outcome of this work, the presented approach may constitute a helpful solution for the industry as well as other domains such as medicine.

Who is a 'healthy subject'?-consensus results on pivotal eligibility criteria for clinical trials.

INTRODUCTION/METHODS: A discussion forum was hosted by the German not-for-profit Association for Applied Human Pharmacology (AGAH e.V.) to critically review key eligibility criteria and stopping rules for clinical trials with healthy subjects, enrolling stakeholders from the pharmaceutical industry, contract research organisations, academia, ethics committees and competent authority. RESULTS: Pivotal eligibility criteria were defined for trials with new investigational medicinal products (IMPs) or with clinically established IMPs. In general, a pulse rate ranging between 50 and 90 beats/min is recommended for first-in-human (FIH) trials, while wider ranges seem acceptable for trials with clinically established IMPs, provided there are no indications of thyroid dysfunction. Hepatic laboratory parameters not to exceed the upper limit of normal (ULN) comprise ALT (alanine aminotransferase) and AST (aspartate aminotransferase) in FIH trials, whereas slight elevations (10% above ULN) seem acceptable in trials with clinically established IMPs without known hepatotoxicity. A normal renal function is required for any clinical trial in healthy subjects. A risk-adapted approach for stopping rules was adopted. Stopping rules for an individual subject are one adverse event of severe intensity or one serious adverse event. In case of a severe adverse event, some stakeholders demand a causal relationship with the IMP (i.e. an adverse reaction). Stopping rules for a cohort are one serious adverse reaction or ≥50% of subjects experiencing any adverse reaction of moderate or severe intensity. CONSEQUENCES: The application of this consensus resulted in a reduction in protocol deficiencies issued by the competent authority.

Effect of netupitant, a highly selective NK1 receptor antagonist, on the pharmacokinetics of palonosetron and impact of the fixed dose combination of netupitant and palonosetron when coadministered with ketoconazole, rifampicin, and oral contraceptives.

OBJECTIVES: Neurokinin-1 receptor antagonists (NK1 RAs) are commonly coadministered with a 5-HT3 RA such as palonosetron to prevent nausea and vomiting induced by chemotherapy. Netupitant, a new highly selective NK1 RA, is both a substrate for and a moderate inhibitor of CYP3A4. Three studies were designed to evaluate the potential drug-drug interaction of netupitant with palonosetron and of the fixed dose combination of netupitant and palonosetron, NEPA, with an inhibitor (ketoconazole), an inducer (rifampicin) and a substrate (oral contraceptives) of CYP3A4. METHODS: Study 1 was a three-way crossover in 18 healthy subjects receiving netupitant alone, palonosetron alone, and the combination of both antiemetics. Studies 2 and 3 were two-way crossover trials where healthy subjects received NEPA (the fixed dose combination of netupitant and palonosetron). In study 2, 36 subjects received NEPA alone (day 1) and in combination with ketoconazole or rifampicin. In study 3, 24 healthy women received ethinylestradiol/levonorgestrel alone or in combination with NEPA (day 1). RESULTS: There were no significant pharmacokinetic interactions between netupitant and palonosetron. Ketoconazole increased netupitant area under curve (AUC) by 140 % and C max by 25 %. Rifampicin decreased netupitant AUC by 83 % and C max by 62 %. NEPA did not significantly affect exposure to ethinylestradiol, while systemic exposure to levonorgestrel increased by 40 %, but this was not considered clinically relevant. CONCLUSIONS: There were no clinically relevant interactions between netupitant and palonosetron, or between NEPA and oral contraceptives. The coadministration of NEPA with inhibitors or inducers of CYP3A4 may require dose adjustments. Treatments were well tolerated.

Smartphone-based behaviour analysis for challenging behaviour in intellectual and developmental disabilities and autism spectrum disorder - Study protocol for the ProVIA trial.

Background: Challenging behaviour (CB) comprises various forms of aggressive and problematic behaviours frequently occurring in children with intellectual and developmental disability (IDD) or autism spectrum disorder (ASD). CB often arises from impaired communication or problem solving skills. It is often met with coercive measure due to a lack of alternative strategies on the part of the caregiver, while it also impacts on the caregivers due to the exposure to physical harm and high levels of stress. Within the ProVIA project we developed a smartphone-based tool for caregivers of children with IDD and/or ASD to prevent and modify CB. The ProVIA app systematically helps caregivers to identify specific causes of CB and provides individualised practical guidance to prevent CB and consecutive coercive measures, thus aiming to improve the health and well-being of the children and caregivers. Methods: In this uncontrolled open trial we will enrol N = 25 caregivers of children aged 3-11 years with a diagnosis of IDD and/or ASD. Participants will use the ProVIA-Kids app for 8 weeks. During the intervention phase, participants will conduct behaviour analyses after each instance of CB. The app will summarise the identified putative causes for the CB in each situation, and provide recommendations regarding the handling and prevention of CB. Furthermore, the app will aggregate data from all available behaviour analyses and identify the most relevant (i.e., most frequently reported) risk factors. Measurement points are at baseline (T0), after the intervention (T1) and 12 weeks after the end of the intervention (follow-up; T2). The primary outcome is the absolute change in parental stress (EBI total scale) between T0 and T1. Further aspects of interest are changes in CB severity and frequency, caregiver mood, satisfaction with the parenting role (EFB-K total scale) and experienced parenting competence (FKE total scale). Pre-post comparisons will be analysed with paired sample t-tests. Discussion: ProVIA is pioneering structured behaviour analysis via smartphone, assessing predefined causes of CB and providing feedback and recommendations. If this approach proves successful, the ProVIA-Kids app will be a valuable tool for caregivers to prevent CB and improve their own as well as the children's quality of life. Trial registration: The study is registered at https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_IDDRKS00029039 (registered May 31, 2022).

Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios.

In medicine or industry, the analysis of high-dimensional data sets is increasingly required. However, available technical solutions are often complex to use. Therefore, new approaches like immersive analytics are welcome. Immersive analytics promise to experience high-dimensional data sets in a convenient manner for various user groups and data sets. Technically, virtual-reality devices are used to enable immersive analytics. In Industry 4.0, for example, scenarios like the identification of outliers or anomalies in high-dimensional data sets are pursued goals of immersive analytics. In this context, two important questions should be addressed for any developed technical solution on immersive analytics: First, is the technical solutions being helpful or not? Second, is the bodily experience of the technical solution positive or negative? The first question aims at the general feasibility of a technical solution, while the second one aims at the wearing comfort. Extant studies and protocols, which systematically address these questions are still rare. In this work, a study protocol is presented, which mainly investigates the usability for immersive analytics in Industry 4.0 scenarios. Specifically, the protocol is based on four pillars. First, it categorizes users based on previous experiences. Second, tasks are presented, which can be used to evaluate the feasibility of the technical solution. Third, measures are presented, which quantify the learning effect of a user. Fourth, a questionnaire evaluates the stress level when performing tasks. Based on these pillars, a technical setting was implemented that uses mixed reality smartglasses to apply the study protocol. The results of the conducted study show the applicability of the protocol on the one hand and the feasibility of immersive analytics in Industry 4.0 scenarios on the other. The presented protocol includes a discussion of discovered limitations.

Safety, Tolerability and Pharmacokinetics of Oral BI 425809, a Glycine Transporter 1 Inhibitor, in Healthy Male Volunteers: A Partially Randomised, Single-Blind, Placebo-Controlled, First-in-Human Study.

BACKGROUND AND OBJECTIVES: Schizophrenia and Alzheimer's disease are characterised by glutamatergic pathway abnormalities related to N-methyl-D-aspartate (NMDA) receptor hypofunction and cognitive impairment. Glycine is an NMDA receptor co-agonist; inhibition of glycine transporter 1 (GlyT1) should improve NMDA receptor hypofunction. This study evaluated safety and pharmacokinetic properties of BI 425809-a potent and selective GlyT1 inhibitor. METHODS: In the single-rising dose (SRD) component of this study, subjects were randomised to a single dose of BI 425809 [doses (mg): 0.5, 1, 2, 5, 10, 25, 50, 100 and 150], or placebo. The bioavailability/food effect (BA/FE) component investigated BI 425809 pharmacokinetics following single dosing (25-mg tablet) after overnight fasting or with a high-calorie meal or as solution (25 mg) after overnight fasting. RESULTS: Overall, 33/83 (39.8%) subjects had ≥ 1 treatment-related adverse event (AE); there were no deaths or serious AEs. Reported SRD part AEs trended towards dose dependency, occurring at the higher doses (mostly central nervous system related). BI 425809 plasma concentration-time profiles were similarly shaped across all doses and plasma exposure increased proportional to dose. In the BA/FE component, geometric mean ratios for the area under the concentration-time curve from time zero to the last measurable concentration and the maximum plasma concentration for tablet fasted versus solution fasted were 80.5 and 50.0%, respectively, and for tablet fed versus fasted were 125.9 and 142.1%, respectively. CONCLUSION: BI 425809 was generally well-tolerated at doses expected to be clinically relevant. The AE profile suggested possible GlyT1-inhibiting effects. CLINICAL TRIAL IDENTIFIER: NCT02068690.

Effect of Steady-State Faldaprevir on Pharmacokinetics of Atorvastatin or Rosuvastatin in Healthy Volunteers: A Prospective Open-Label, Fixed-Sequence Crossover Study.

Faldaprevir (FDV) is a potent, orally administered inhibitor of hepatitis C virus protease. It inhibits multiple cytochrome P-450 enzymes and multiple membrane transporters. The objective of this study was to evaluate the effect of steady-state faldaprevir on the pharmacokinetics (PK) of a single dose of atorvastatin or rosuvastatin. In this single-center, open-label, fixed-sequence crossover study, 33 healthy adult male and female volunteers were given either atorvastatin 10 mg (n = 16) or rosuvastatin 10 mg (n = 17) on day 1. Subjects subsequently received 240 mg twice daily of faldaprevir (loading dose) on day 5, followed by 240 mg faldaprevir once daily from day 6 to day 10, with an additional single dose of atorvastatin (10 mg) or rosuvastatin (10 mg) given on day 10. PK samples for the statins were collected on days 1-3 and days 10-12. Concomitant administration with faldaprevir led to approximately 9-fold and 34-fold increases in AUC0-∞ and Cmax , respectively, of atorvastatin and approximately 15-fold and 33-fold increases in AUC0-∞ and Cmax , respectively, of rosuvastatin, compared with the statins given alone. Exposure to the major metabolites (ortho-hydroxyatorvastatin and N-desmethylrosuvastatin) was increased to a similar magnitude as that of the parent compounds. The marked drug-drug interaction observed is most likely related to the inhibitory effects of faldaprevir on transporters, particularly hepatic uptake transporters such as OTAP1B1 and OATP1B3. Given the significant increase in exposure to statins in healthy volunteers, coadministration of faldaprevir with statins should be avoided.

Evaluation of the effect of food and age on the pharmacokinetics of oral netupitant and palonosetron in healthy subjects: A randomized, open-label, crossover phase 1 study.

Antiemetic treatment compliance is important to prevent chemotherapy-induced nausea and vomiting, a feared chemotherapy side effect. NEPA, a new oral fixed combination of netupitant, a highly selective NK1 receptor antagonist (RA), and palonosetron, a second-generation 5-HT3 RA, targets dual antiemetic pathways with a single dose. This study investigated the effect of food intake and age on NEPA pharmacokinetics (PK) and safety. In this open-label, single-center, randomized, phase 1 study, 24 adults (18-45 years) received NEPA in a fed or fasted state during the first treatment period and in the alternative state in the next treatment period. Twelve elderly subjects (≥65 years) received NEPA in a fasted state. Blood samples were taken for netupitant and palonosetron PK analysis. In the fed condition, netupitant plasma exposure increased, whereas palonosetron PK parameters were not affected. Furthermore, elderly subjects showed increased netupitant and palonosetron exposure compared with adults. All adverse events were mild/moderate, with constipation and headache the most common. Although food intake and age altered NEPA PK, dose adjustments were not needed, as netupitant and palonosetron exposure increases did not lead to safety concerns in healthy subjects.

The influence of the lower patellar pole in the pathogenesis of chronic patellar tendinopathy.

Resection of the lower patellar pole provides good results in the treatment of jumper's knee. Therefore we hypothesized that the length of the lower patellar pole is increased in patients with chronic patellar tendinopathy. Cohort study, level of evidence 2. Between 2000 and 2005, 25 patients with chronic patellar tendinopathy underwent conservative and surgical treatment in our clinic. All of them had preoperative MRI were three independent examiners measured the Caton Index, the length and the ratio of the articular and non-articular patellar surface, tendon length and thickness and the thickness and length of the hypodens lesions in the patellar tendon. The measurements were compared with 50 MRI of a control group with no clinical patellofemoral disorders or patellar tendinopathy. Significant changes in tendon thickness (9.42+/-2.87 vs. 4.88+/-1.13; P<0.0001), a longer non-articular surface of the patella (10.62+/-2.86 vs. 7.098+/-2.53; P<0.0001) and significant higher ratio between the articular and the non-articular patellar surface (0.32 vs. 0.24; P<0.0001) were found in the jumper's knee group. No significant changes were seen in the length of the articular surface or the Caton Index. The development of chronic patellar tendinopathy in athletes might be associated with a longer lower patellar pole as patients with jumper's knee showed a longer non-articular patellar surface compared with the control group.