Printing of polymer parts via digital light processing (DLP) is an established technology to produce functional complex parts within a short period of time. Within recent years this technology has advanced in even higher geometrical accuracy of the parts since printers and materials were constantly improved. Nowadays, it is possible to print parts with features in micro- (µm) or even nanoscale (nm), opening new fields of application and further improvement to already existing parts. Similar to stereolithography (SLA), DLP applies UV light to harden a photopolymer resin in a layer-by-layer process. This enables printing parts with complex geometries such as cavities, implying the resin can later exit the part. However, DLP has an advantage over other 3D-printing technologies when it comes to creating cavities or the printing of overhang structures in general. Since in DLP the entire layer is hardened at once, less support structure is needed to achieve a uniform, stable layer. In consequence, this opens the design option to print micro cavities without any support structures needed. This paper highlights the process of micro DLP printing of polymer parts, focusing on the influence of the most relevant parameters on the successful print of overhang structures. Therefore, the paper presents an experimental analysis, investigating the effects of relevant printing parameters of an overhang on the dimensional accuracy of the resulting parts. The results show a significant dependence of the bridges (overhangs) on gaps size and curing time, and the deformation of the bridges are in the opposite sides of the parts.

In order to tackle today's grand challenges in society and reach sustainable development goals, innovation needs to take a comprehensive look at value creation and human well-being. Social systems theory suggests that value creation and well-being can be addressed from the perspectives of various functional systems that attribute meaning on the basis of different social operations, such as economy, health, art, etc. On the example of smart services as a key digital technology, we study how science fiction affects the number of these functional systems referenced in design. We compare smart service design activities performed during eight ideation and prototyping workshops. Half of the workshops used a conventional value proposition canvassing approach to address customer tasks, pains and gains. The others used science fiction plots for dramatic storytelling about smart services. Overall, 29 separate smart service design projects were performed during the workshops. Using qualitative content analysis, references to different functional systems are identified. The findings indicate that science fiction inspires references to more functional systems and highlights tensions between different forms of value creation and aspects of well-being that are essential for tackling grand challenges.

KI-Sprachmodelle wie ChatGPT gewinnen an Bedeutung. Zwar liefern sie noch weniger Traffic als Suchmaschinen, doch ihr Einfluss auf die frühen Phasen der Customer Journey steigt. Auch die Abdeckung transaktionaler Journey-Elemente ist nur eine Frage der Zeit.

This study explores a resource-based perspective on subjective wellbeing in educational contexts by introducing the concept of happiness capital. Building on the educational and learning capital approach, we adapted existing measures to assess how personal and environmental resources contribute to students’ wellbeing. In a sample of 1,528 Egyptian secondary school students, perceived happiness capital significantly predicted life satisfaction, positive and negative emotions across all age groups. These findings suggest that the same resource structures supporting learning can foster emotional flourishing. We briefly discuss implications for resource-based models of wellbeing in education and propose directions for future research.

 

• Vor dem Hintergrund sinkender Studierendenzahlen und des Fachkräftemangels in den technischen Berufen in Deutschland, rekrutieren die Hochschulen in Bayern zunehmend Studierende aus dem Ausland. Dabei stoßen die angebotenen internationalen Studiengänge besonders bei Studierenden aus Indien auf großes Interesse. Andersartige Kompetenzprofile aus dem außereuropäischen Bachelorstudium in Kombination mit sehr hohen Erwartungen der Studierenden an ein Masterstudium in Deutschland führen zu enormen Herausforderungen bei allen Beteiligten. Förderlich für den erfolgreichen Studienverlauf ist es, Maßnahmen zur Gruppendurchmischung zwischen ausländischen und deutschen Studierenden wie internationale Postersessions und gemeinsame Studienangebote zu implementieren. Darüber hinaus ist es erforderlich, Regeln der guten wissenschaftlichen Praxis klar zu kommunizieren und deren Befolgung einzufordern. Nicht zuletzt ist die Stärkung der Sprachkompetenz ein Schlüssel für ein erfolgreiches Studium.

Sport-tracking applications can enhance physical activity but may also induce stress through social comparison. This study examines how social comparison features influence user experience (UX), focusing on motivation, stress, and mental well-being. A survey of 101 German sport-tracking app users assessed intrinsic and extrinsic motivation, perceived stress, self-efficacy, enjoyment, social comparison orientation, and UX. Results reveal that higher social comparison consistently lowers intrinsic motivation, raises extrinsic motivation, and increases stress levels, while positive UX boosts intrinsic motivation and enjoyment and indirectly buffers stress. Notably, app designs prioritizing mastery and personal progress over competitive rankings foster autonomy, competence, and relatedness, supporting mental health and long-term adherence. These findings highlight the ambivalent effects of social features and underscore the need for sport-tracking apps to minimize harmful comparisons and promote self-determined motivation through supportive, user-friendly features. Practical implications include designing for sustainable engagement and well-being rather than exclusive competition.

Emotion AI is transforming how emotional dynamics are integrated into consumer research and product design. By detecting and interpreting emotional cues from facial expressions, voice, and behaviour, it enables emotionally intelligent systems that move beyond conventional user interaction models. This chapter examines Emotion AI as both a methodological tool and a design principle, offering deeper insights into user sentiment and supporting the creation of hedonic experiences – what we term digital empathy. Grounded in established emotion theories and recent technological advances, the chapter explores cross-sector applications and reflects on the ethical implications surrounding the use of emotional data.

Background

The Freiburg Mindfulness Inventory (FMI) in its short form is one of the most frequently used instruments in research to measure self-attributed mindfulness levels. Despite the widespread use, there is no calibration sample available until now. Thus, we decided to calibrate it in a representative German sample as norm values are of relevance for clinicians and researchers alike. In addition, we tried to replicate the instruments’ psychometric properties.

Methods

A sample of 1,012 respondents was recruited from a commercial online panel, approximating a representative sample of the German population. Participants filled in the FMI-14 (short from). We performed psychometric analyses and calculated a Confirmatory Factor Analysis (CFA). We also computed a measurement invariance analysis and a LASSO regression to identify population variables that predict FMI scores. To gauge external validity of the instrument, we also presented the FMI together with four items of the Patient Health Questionnaire (PHQ-4).

Results

We obtained the best psychometric properties with a revised version of the FMI-13R, where the only negatively coded item was removed due to lack of fit. McDonald’s Omega was found to be 0.88 and the mean item-scale intercorrelation was 0.36. The construct is unidimensional, with two highly correlated subconstructs, Presence and Acceptance (r = 0.93), which can be separated for conceptual reasons if desired. The CFA supported these models. Age and gender stratified norm scores were calculated and reported. Regression analyses and partial correlation analyses showed negative correlation of FMI-13R scores with measures of anxiety and depression, as expected, and thereby support our previous findings that the instrument is valid and that the Acceptance component of mindfulness is the one that is associated with positive effects on health-related parameters.

Conclusion

The FMI-13R is a psychometrically sound and valid instrument for the assessment of mindfulness. Norm scores can now be used by clinicians and researchers to classify individuals or samples into a range of values compared to the German population.

In additive manufacturing, the optimisation of process parameters to simultaneously enhance both mechanical and geometrical properties remains a significant challenge. This study presents a comparative analysis between two distinct approaches to multi-response optimisation: a hybrid method combining Artificial Neural Networks with Pattern Search Algorithm, and the traditional Response Surface Methodology. Both methods were applied to optimise the process parameters of Fused Filament Fabrication using Polylactic Acid. The hybrid ANN + PSA model was used to predict process outputs and optimise printing parameters, while RSM employed a statistical approach to identify optimal parameter combinations through designed experiments. Results show that ANN + PSA achieved better outcomes with a maximum tensile strength of 61.88 MPa and dimensional deviations within 3%, compared to RSM's tensile strength of 53.05 MPa and deviations up to 4%. The ANN + PSA model demonstrated higher predictive accuracy with an R² of 94.34% during training and 91.34% during evaluation, versus RSM’s R² of 90.5% for tensile strength prediction. Additionally, ANN + PSA consistently required fewer experimental trials due to its integration with the Pattern Search Algorithm, improving computational efficiency. The findings demonstrate that ANN + PSA is computationally efficient for scenarios with fewer experimental trials, while RSM offers a more detailed understanding of interaction effects. The comparative insights from this study contribute to enhanced multi-response optimisation strategies in additive manufacturing.

·       Hyperpersonalisierung und Extended Reality (XR) verändern die Customer Journey

·       KI-gestützte Personalisierung gestaltet Markenkommunikation und Kundenerlebnisse emotionaler und interaktiver

·       Extended Reality (XR) eröffnen neue Dimensionen immersiver Markenerlebnisse

·       Immersive Consumer Experience bindet Konsumenten stärker an Marken und erleichtern die Kaufentscheidung

Medical products such as mesh implants should demonstrate high material quality and long service life in different
environments over several years. Polypropylene (PP) is a thermoplastic widely used for medical applications due to its
mechanical properties, biocompatibility, and chemical resistance. This study examines the effect of thermal treatment on
the mechanical, thermal, and chemical properties of polypropylene homopolymer (PP-H) and random copolymer (PP-
RC), with and without the addition of palmitic acid (PA) to simulate lipid exposure during implantation. Mechanical and
thermal properties of PA-treated PP-H as analysed by tensile test, differential scanning calorimetry, and thermogravimetric
analysis, showed a higher tensile strength, elastic modulus, and thermal stability than PP-RC. Fourier-transform-infrared
spectroscopy detected no significant chemical changes after thermal treatment, whereas in Raman spectroscopy changes in
the intensity of the peaks and new peaks due to PA were visible. In conclusion, PA incubation accelerated material deg-
radation, with PP-H demonstrating superior stability in the mechanical and thermal properties under the tested conditions.

Der Beitrag stellt den Entwicklungsprozess des im Projekt LeadCom entstandenen Selbstlernkurses Videokonferenznutzung zur kollegialen Kommunikation und Kooperation dar und zeigt auf, warum diese Fortbildung zum Thema Videokonferenzen in außerunterrichtlichen Situationen für eine zeitgemäße Schulentwicklung relevant ist. Einerseits wurde der Kurs mit dem Ziel konstruiert, durch eine kompetente Nutzung von virtuellen Meetings im Schulkontext, eine moderne und effektive Zusammenarbeit im Lehrerkollegium zu fördern und so den sich verändernden Ansprüchen einer zunehmend digitalisierten Welt gerecht zu werden. Andererseits soll die Nutzung des Selbstlernkurses auch dazu beitragen, dass Lehrkräfte und Schulleitungen sich digital kompetent und selbstwirksam im Umgang mit digitalen Kommunikationsmedien erleben. Als Transferziel sollten die Einstellungen und Erwartungen von Lehrkräften gegenüber Informations- und Kommunikationstechnologien (ICT) und die Nutzung von ICT für schulinterne Kooperation die Nutzung von ICT im Unterricht sowie die digitale Kompetenzentwicklung von Schülerinnen und Schülern positiv beeinflussen (u.a. Drossel et al., 2016; Fraillon et al., 2020). Die Entwicklung des Selbstlernkurses fußte dabei unter anderem auf dem weiterentwickelten Technologieakzeptanzmodell von Venkatesh et al. (2003, 2012), der Unified Theory of Acceptance and Use of Technology (UTAUT). In einer eng mit dem Entwicklungsprozess der Fortbildungseinheit durchgeführten quantitativen Studie wurden anhand des UTAUT-Modells Einstellungen und Erwartungen von Lehrkräften in Bezug auf die Nutzung von Videokonferenzen in außerunterrichtlichen Kommunikations- und Kooperationssituationen untersucht. Der Beitrag wird aufzeigen, wie sowohl die theoretischen Überlegungen aus dem UTAUT-Modell als auch in Teilen die Ergebnisse der Studie in die Konstruktion des Selbstlernkurses eingeflossen sind.