Introduction: There is neither strong evidence on effective treatments for patients with chronic back pain (CBP) and depressive disorder nor sufficiently available mental health care offers. Objective: The aim is to assess the effectiveness of internet- and mobile-based interventions (IMI) as a scalable approach for treating depression in a routine care setting. Methods: This is an observer-masked, multicenter, pragmatic randomized controlled trial with a randomization ratio of 1:1.Patients with CBP and diagnosed depressive disorder (mild to moderate severity) were recruited from 82 orthopedic rehabilitation clinics across Germany. The intervention group (IG) received a guided depression IMI tailored to CBP next to treatment-as-usual (TAU; including medication), while the control group (CG) received TAU. The primary outcome was observer-masked clinician-rated Hamilton depression severity (9-week follow-up). The secondary outcomes were: further depression outcomes, pain-related outcomes, health-related quality of life, and work capacity. Biostatistician blinded analyses using regression models were conducted by intention-to-treat and per protocol analysis. Results: Between October 2015 and July 2017, we randomly assigned 210 participants (IG, n = 105; CG, n = 105), mostly with only a mild pain intensity but substantial pain disability. No statistically significant difference in depression severity between IG and CG was observed at the 9-week follow-up (β = –0.19, 95% CI –0.43 to 0.05). Explorative secondary depression (4/9) and pain-related (4/6) outcomes were in part significant (p < 0.05). Health-related quality of life was significantly higher in the IG. No differences were found in work capacity. Conclusion: The results indicate that an IMI for patients with CBP and depression in a routine care setting has limited impact on depression. Benefits in pain and health-related outcomes suggest that an IMI might still be a useful measure to improve routine care.

Laser-Powder Bed Fusion brings new possibilities for the design of parts, e.g., cutter shafts with integrated cooling channels close to the contour. However, there are new challenges to dimensional accuracy in the production of thin-walled components, e.g., heat exchangers. High degrees of dimensional accuracy are necessary for the production of functional components. The aim is to already achieve these during the process, to reduce post-processing costs and time. In this work, thin-walled ring specimens of H13 tool steel are produced and used for the analysis of dimensional accuracy and residual stresses. Two different scanning strategies were evaluated. One is a stripe scan strategy, which was automatically generated and provided by the machine manufacturer, and a (manually designed) sectional scan strategy. The ring segment strategy is designed by manually segmenting the geometry, which results in a longer preparation time. The samples were printed in different diameters and analyzed with respect to the degree of accuracy and residual stresses. The dimensional accuracy of ring specimens could be improved by up to 81% with the introduced sectional strategy compared to the standard approach.

Experimental analyses are performed to determine thermal conductivity, thermal diffusivity and volumetric specific heat with transient plane source method on hollow sphere structures. Single-sided testing is used on different samples and different surfaces. Results dependency on the surface is observed.

In recent years, additive manufacturing has attracted great attention worldwide. This new production process makes it possible to manufacture highly comple