Zoekresultaten

Collaborative Robots Entering the Factory Floor

Using the latest industrial robot technology, the collaborative robot (cobot), industrial manufacturers work towards high-mix low-volume production systems that could satisfy a diversifying customer demand. As the utilization of the cobot’s potential depends on the dynamic interaction with operators, one would expect HR professionals to play a central role in this implementation process. However, cobot-related literature is unanimous: HR is not involved. This is in line with the results of our study in 2019 on seventeen cobot experiments in Dutch industrial manufacturing companies. To explore what human cobot collaboration emerges when engineers and line managers take the lead in their design, we revisited the data from our previous interview study (N=53). HR was absent in all implementations. We found that line managers and engineers prepared operators for rigid human-cobot collaborations that were aimed at getting the cobot to work, enhancing production efficiency and handling a few batches of mass-produced goods (low-mix, high-volume). Furthermore, the collaborations all showed signs of being difficult to sustain over time and posed a direct threat to operators’ well-being. To protect operators’ future of work and build towards interdependent human-cobot collaboration suitable for high-mix low-volume production, we propose an approach in which operators themselves, and HR too, are much more involved in the cobot implementation process. Operators should be allowed and supported to design, program, operate, and repair as much of their human-cobot workstations themselves as possible. To support this, HR has to familiarize itself with the cobot technology, secure operators’ decision latitude, facilitate the required support, and become the work design expert that helps operators co-design sustainable cobot applications that optimally utilize the strengths of both man and machine.

How Operators Design Their Human-Cobot Interdependencies

Cross-Border Business Development in the Dutch-German Borderland

Like a marker pen on a map, the Covid-19 pandemic drastically highlighted the persisting existence of borders that used to play an ever decreasing role in people´s perception and behavior over the last decades. Yes, inner European borders are open in normal times. Yes, people, goods, services and ideas are crossing the border between Germany and the Netherlands freely. Yet we see that the border can turn into a barrier again quickly and effectively and it does so in many dimensions, some of them being not easily visible. Barriers hinder growth, development and exchange and in spite of our progress in creating a borderless Europe, borders still create barriers in many domains. Differing labor law, social security and tax systems, heterogeneous education models, small and big cultural differences, language barriers and more can impose severe limitations on people and businesses as they cross the border to travel, shop, work, hire, produce, buy, sell, study and research. Borders are of all times and will therefore always exist. But as they did so for a long time, huge opportunities can be found in overcoming the barriers they create. The border must not necessarily be a dividing line between two systems. It has the potential to become a center of growth and progress that build on joint efforts, cross-border cooperation, mutual learning and healthy competition. Developing this inherent potential of border regions asks for politics, businesses and research & education on both sides of the border to work together. The research group Cross-Border Business Development at Fontys University of Applied Science in Venlo conducts applied research on the impact of the national border on people and businesses in the Dutch-German border area. Students, employees, border commuters, entrepreneurs and employers all face opportunities as well as challenges due to the border. In collaboration with these stakeholders, the research chair aims to create knowledge and provide solutions towards a Dutch-German labor market, an innovative Dutch-German borderland and a futureproof Cross-Border economic ecosystem. This collection is not about the borderland in times of COVID-19. Giving meaning to the borderland is an ongoing process that started long before the pandemic and will continue far beyond. The links that have been established across the border and those that will in the future are multifaceted and so are the topics in this collection. Vincent Pijnenburg outlines a broader and introductory perspective on the dynamics in the Dutch-German borderland.. Carla Arts observes shopping behavior of cross-border consumers in the Euregion Rhine-Meuse-North. Jan Lucas explores the interdependencies of the Dutch and German economies. Jean Louis Steevensz presents a cross-border co-creation servitization project between a Dutch supplier and a German customer. Vincent Pijnenburg and Patrick Szillat analyze the exitence of clusters in the Dutch-German borderland. Christina Masch and Janina Ulrich provide research on students job search preferences with a focus on the cross-border labor market. Sonja Floto-Stammen and Natalia Naranjo-Guevara contribute a study of the market for insect-based food in Germany and the Netherlands. Niklas Meisel investigates the differences in the German and Dutch response to the Covid-19 crisis. Finally, Tolga Yildiz and Patrick Szillat show differences in product-orientation and customer-orientation between Dutch and German small and medium sized companies. This collection shows how rich and different the links across the border are and how manifold the perspectives and fields for a cross-border approach to regional development can be. This publication is as well an invitation. Grasping the opportunities that the border location entails requires cooperation across professional fields and scientific disciplines, between politics, business and researchers. It needs the contact with and the contribution of the people in the region. So do what we strive for with our cross-border research agenda: connect!

Identifying critically ill patients with low muscle mass

Background & aims: Low muscle mass and -quality on ICU admission, as assessed by muscle area and -density on CT-scanning at lumbar level 3 (L3), are associated with increased mortality. However, CT-scan analysis is not feasible for standard care. Bioelectrical impedance analysis (BIA) assesses body composition by incorporating the raw measurements resistance, reactance, and phase angle in equations. Our purpose was to compare BIA- and CT-derived muscle mass, to determine whether BIA identified the patients with low skeletal muscle area on CT-scan, and to determine the relation between raw BIA and raw CT measurements. Methods: This prospective observational study included adult intensive care patients with an abdominal CT-scan. CT-scans were analysed at L3 level for skeletal muscle area (cm2) and skeletal muscle density (Hounsfield Units). Muscle area was converted to muscle mass (kg) using the Shen equation (MMCT). BIA was performed within 72 h of the CT-scan. BIA-derived muscle mass was calculated by three equations: Talluri (MMTalluri), Janssen (MMJanssen), and Kyle (MMKyle). To compare BIA- and CT-derived muscle mass correlations, bias, and limits of agreement were calculated. To test whether BIA identifies low skeletal muscle area on CT-scan, ROC-curves were constructed. Furthermore, raw BIA and CT measurements, were correlated and raw CT-measurements were compared between groups with normal and low phase angle. Results: 110 patients were included. Mean age 59 ± 17 years, mean APACHE II score 17 (11–25); 68% male. MMTalluri and MMJanssen were significantly higher (36.0 ± 9.9 kg and 31.5 ± 7.8 kg, respectively) and MMKyle significantly lower (25.2 ± 5.6 kg) than MMCT (29.2 ± 6.7 kg). For all BIA-derived muscle mass equations, a proportional bias was apparent with increasing disagreement at higher muscle mass. MMTalluri correlated strongest with CT-derived muscle mass (r = 0.834, p < 0.001) and had good discriminative capacity to identify patients with low skeletal muscle area on CT-scan (AUC: 0.919 for males; 0.912 for females). Of the raw measurements, phase angle and skeletal muscle density correlated best (r = 0.701, p < 0.001). CT-derived skeletal muscle area and -density were significantly lower in patients with low compared to normal phase angle. Conclusions: Although correlated, absolute values of BIA- and CT-derived muscle mass disagree, especially in the high muscle mass range. However, BIA and CT identified the same critically ill population with low skeletal muscle area on CT-scan. Furthermore, low phase angle corresponded to low skeletal muscle area and -density. Trial registration: ClinicalTrials.gov (NCT02555670).

Association of sleep deprivation with speech volume and pitch

Optimal Dosing and Timing of High-Dose Corticosteroid Therapy in Hospitalized Patients With COVID-19

Background:In hospitalized patients with COVID-19, the dosing and timing of corticosteroids vary widely. Low-dose dexamethasone therapy reduces mortality in patients requiring respiratory support, but it remains unclear how to treat patients when this therapy fails. In critically ill patients, high-dose corticosteroids are often administered as salvage late in the disease course, whereas earlier administration may be more beneficial in preventing disease progression. Previous research has revealed that increased levels of various biomarkers are associated with mortality, and whole blood transcriptome sequencing has the ability to identify host factors predisposing to critical illness in patients with COVID-19.Objective:Our goal is to determine the most optimal dosing and timing of corticosteroid therapy and to provide a basis for personalized corticosteroid treatment regimens to reduce morbidity and mortality in hospitalized patients with COVID-19.Methods:This is a retrospective, observational, multicenter study that includes adult patients who were hospitalized due to COVID-19 in the Netherlands. We will use the differences in therapeutic strategies between hospitals (per protocol high-dose corticosteroids or not) over time to determine whether high-dose corticosteroids have an effect on the following outcome measures: mechanical ventilation or high-flow nasal cannula therapy, in-hospital mortality, and 28-day survival. We will also explore biomarker profiles in serum and bronchoalveolar lavage fluid and use whole blood transcriptome analysis to determine factors that influence the relationship between high-dose corticosteroids and outcome. Existing databases that contain routinely collected electronic data during ward and intensive care admissions, as well as existing biobanks, will be used. We will apply longitudinal modeling appropriate for each data structure to answer the research questions at hand.Results:As of April 2023, data have been collected for a total of 1500 patients, with data collection anticipated to be completed by December 2023. We expect the first results to be available in early 2024.Conclusions:This study protocol presents a strategy to investigate the effect of high-dose corticosteroids throughout the entire clinical course of hospitalized patients with COVID-19, from hospital admission to the ward or intensive care unit until hospital discharge. Moreover, our exploration of biomarker and gene expression profiles for targeted corticosteroid therapy represents a first step towards personalized COVID-19 corticosteroid treatment.Trial Registration:ClinicalTrials.gov NCT05403359; https://clinicaltrials.gov/ct2/show/NCT05403359International Registered Report Identifier (IRRID):DERR1-10.2196/48183