Potentials and challenges of additive manufacturing using highly transparent silicone materials

The research in additive manufacturing using highly transparent silicone for optical applications is still in its early stages. This contribution is aiming to investigate potentials and challenges in additive manufacturing using silicone and to identify a suitable manufacturing concept to fabricate highly transparent optical elements.Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) in Germany’s Excellence Strategy within the Cluster of Excellence PhoenixD (EXC 2122, Project ID 390833453) and funded by EFRE - Nbank within the project “GROTESK - Generative Fertigung optischer, ther-maler und struktureller Komponenten” (ZW6-85018307, ZW6-85017815, ZW6-85017913, ZW6-85018048)

The Impact of Semantic Context Cues on the User Acceptance of Tag Recommendations: An Online Study

In this paper, we present the results of an online study with the aim to shed light on the impact that semantic context cues have on the user acceptance of tag recommendations. Therefore, we conducted a work-integrated social bookmarking scenario with 17 university employees in order to compare the user acceptance of a context-aware tag recommendation algorithm called 3Layers with the user acceptance of a simple popularity-based baseline. In this scenario, we validated and verified the hypothesis that semantic context cues have a higher impact on the user acceptance of tag recommendations in a collaborative tagging setting than in an individual tagging setting. With this paper, we contribute to the sparse line of research presenting online recommendation studies.Comment: 2 pages, poste

Designing Technologies to Support Professional and Workplace Learning for Situated Practice

The papers in this special section focus on designing technologies to support professional and workplace learning in situated practices. In an era of global, organizational, and technological change, all of which are transforming the world of work, professional and workplace learning are critical for employability and organizational competitiveness. A range of fundamental transformations is changing how people work. Digital technologies are replacing human labor and, at the same time, are accelerating the expansion of job roles and work practices. Work is becoming increasingly specialized, which means that professionals in collaborative and networked ways across discipline and organization boundaries. In parallel, labor is increasingly decentralized, making decisionmaking more distributed and raising the need for remote communication and collaboration. Subsequently, work is becoming more independent from time and place, as people connect, collaborate, and work via digital technologies. These changes come with a need for substantial and continuous workplace learning, and with the need for changes in how workplace learning happens. Of course, digital technologies are already used to provide learning and training in workplaces. However, most of these learning technologies have been developed for formal education (e.g., K- 12 and higher education) rather than in workplace contexts. There is a need to understand and evidence workplace learning needs and to further develop technologies that can support and scale workplace learning

The Impact of Energy Prices on Green Innovation

Based on patent data and industry specific energy prices for 18 OECD countries over 30 years we investigate on an industry level the impact of energy prices on green innovation activities. Our econometric models show that energy prices and green innovation activities are positively related and that energy prices have a significantly positive impact on the ratio of green innovations to non-green innovations. More concretely, our main model shows that a 10% increase of the average energy prices over the previous five years results in a 3.4% and 4.8% increase of the number of green innovations and the ratio of green innovations to non-green innovations, respectively. We also find that the impact of energy prices increases with an increasing lag between energy prices and innovation activities. Robustness tests confirm the main results

β-Adrenoceptor activation depresses brain inflammation and is neuroprotective in lipopolysaccharide-induced sensitization to oxygen-glucose deprivation in organotypic hippocampal slices

<p>Abstract</p> <p>Background</p> <p>Inflammation acting in synergy with brain ischemia aggravates perinatal ischemic brain damage. The sensitizing effect of pro-inflammatory exposure prior to hypoxia is dependent on signaling by TNF-α through TNF receptor (TNFR) 1. Adrenoceptor (AR) activation is known to modulate the immune response and synaptic transmission. The possible protective effect of <inline-formula><m:math xmlns:m="http://www.w3.org/1998/Math/MathML" name="1742-2094-7-94-i1"><m:mover accent="true"><m:mi>α</m:mi><m:mo>˜</m:mo></m:mover></m:math></inline-formula> and <inline-formula><m:math xmlns:m="http://www.w3.org/1998/Math/MathML" name="1742-2094-7-94-i2"><m:mover accent="true"><m:mi>β</m:mi><m:mo>˜</m:mo></m:mover></m:math></inline-formula>AR activation against neuronal damage caused by tissue ischemia and inflammation, acting in concert, was evaluated in murine hippocampal organotypic slices treated with lipopolysaccharide (LPS) and subsequently subjected to oxygen-glucose deprivation (OGD).</p> <p>Method</p> <p>Hippocampal slices from mice were obtained at P6, and were grown <it>in vitro </it>for 9 days on nitrocellulose membranes. Slices were treated with β1(dobutamine)-, β2(terbutaline)-, α1(phenylephrine)- and α2(clonidine)-AR agonists (5 and 50 μM, respectively) during LPS (1 μg/mL, 24 h) -exposure followed by exposure to OGD (15 min) in a hypoxic chamber. Cell death in the slice CA1 region was assessed by propidium iodide staining of dead cells.</p> <p>Results</p> <p>Exposure to LPS + OGD caused extensive cell death from 4 up to 48 h after reoxygenation. Co-incubation with β1-agonist (50 μM) during LPS exposure before OGD conferred complete protection from cell death (P < 0.001) whereas the β2-agonist (50 μM) was partially protective (p < 0.01). Phenylephrine was weakly protective while no protection was attained by clonidine. Exposure to both β1- and β2-agonist during LPS exposure decreased the levels of secreted TNF-α, IL-6 and monocyte chemoattractant protein-1 and prevented microglia activation in the slices. Dobutamine remained neuroprotective in slices exposed to pure OGD as well as in TNFR1^-/-and TNFR2^-/-slices exposed to LPS followed by OGD.</p> <p>Conclusions</p> <p>Our data demonstrate that activation of both β1- and β2-receptors is neuroprotective and may offer mechanistic insights valuable for development of neuro-protective strategies in neonates.</p

Progress-Oriented Workshops for Doctoral Well-being: Evidence From a Two-Country Design-Based Research

This paper explores an intervention approach (in the form of workshops) focusing on doctoral progress, to address the problems of low emotional well-being experienced by many doctoral candidates. Doctoral education suffers from two severe overlapping problems: high dropout rates and widespread low emotional well-being (e.g., depression or anxiety symptoms). Yet, there are few interventional approaches specifically designed to address them in the doctoral student population. Among structural, psychosocial, and demographic factors influencing these problems, the self-perception of progress has emerged recently as a crucial motivational factor in doctoral persistence. This paper reports on an iterative design-based research study of workshop interventions to foster such perception of progress in doctoral students? everyday practice. We gathered mixed data over four iterations, with a total of 82 doctoral students from multiple disciplines in Spain and Estonia. An approach to preventive interventions that combines research-backed education about mental health and productivity, peer sharing and discussion of experiences, and indicators of progress, as well as self-tracking, analysis, and reflection upon everyday evidence of their own progress. The paper provides initial evidence of the effectiveness of the proposed interventions, across two institutions in two different countries. Further, our data confirms emergent research on the relationships among progress, emotional well-being, and dropout ideation in two new contexts. Finally, the paper also distills design knowledge about doctoral interventions that focus on progress, relevant for doctoral trainers, institutions, and researchers.This research has received funding from the European Union’s Horizon 2020 research and innova-tion programme under grant agreement No. 669074 (CEITER). It has also received funding from the European Union’s Erasmus Plus programme, grant agreement 2019-1-NO01-KA203-060280 (DE-TEL). The Universidad de Valladolid co-authors acknowledge funding of the European Regional Development Fund and the National Research Agency of the Spanish Ministry of Science, Innova-tion, and Universities, under project grant TIN2017-85179-C3-2-R (SmartLET), and PID2020-112584RB-C32, the European Regional Development Fund, and the Regional Government of Cas-tile and Leon, under project grant VA257P18

Requirements for Automotive LiDAR Systems

Light detection and ranging (LiDAR) are fundamental sensors that help driving tasks for autonomous driving at various levels. Commercially available systems come in different specialized design schemes and involve plenty of specifications. In the literature, there are insufficient representations of the technical requirements for LiDAR systems in the automotive context, such as range, detection quality, resolving power, field of view, and eye safety. For this reason, the requirements above require to be derived based on ADAS functions. The requirements for various key LiDAR metrics, including detection range, field of view, angular resolution, and laser safety, are analyzed in this paper. LiDAR systems are available with various radiation patterns that significantly impact on detection range. Therefore, the detection range under various radiation patterns is firstly investigated in this paper. Based on ADAS functions, the required detection range and field of view for LiDAR systems are examined, taking into account various travel speeds to avoid collision and the coverage of the entire lane width. Furthermore, the angular resolution limits are obtained utilizing the KITTI dataset and exemplary 3D detection algorithms. Finally, the maximum detection ranges for the different radiation patterns are compared under the consideration of derived requirements and laser safety