The Relationship Between Poverty and Behavior Problems : Examining the Role of Family and Parental Factors from an Ecological Systems Perspective

The large number of children from low-income households or living in poverty are at increased risk for a range of negative outcomes, including behavior problems. The Family Stress Model is a framework that can be used to describe how poverty may shape the development of behavior problems through its influence on family processes, including parental mental health, parenting, and household environment. While the Family Stress Model has been widely replicated, studies have rarely examined the context of infancy and toddlerhood, during which family-related processes tend to be more impactful in child development. Therefore, the present study evaluated two adaptations of the Family Stress Model in a large, ethnically diverse sample of Early Head Start families (N= 2,835). Specifically, the present study investigated whether poverty, in the form of economic hardships and pressures, contributes to behavior problems in infancy and toddlerhood indirectly through its impact on four family-based risk factors (parental depression, household chaos, parenting stress, and parental sensitivity), as well as whether these factors operate independently or indirectly through parental sensitivity. Results indicated that parental depression, parenting stress, and household chaos mediated relations between economic pressure and parental sensitivity, and that parenting stress and household chaos, but not parental depression, were associated with child behavior problems indirectly through parental sensitivity. Social support was also identified as a buffer against the negative effect of economic pressure on parental depression. Implications for future Family Stress Model research with Early Head Start families, as well as for prevention and intervention approaches, are discussed

Automatic Aorta Segmentation with Heavily Augmented, High-Resolution 3-D ResUNet: Contribution to the SEG.A Challenge

Automatic aorta segmentation from 3-D medical volumes is an important yet difficult task. Several factors make the problem challenging, e.g. the possibility of aortic dissection or the difficulty with segmenting and annotating the small branches. This work presents a contribution by the MedGIFT team to the SEG.A challenge organized during the MICCAI 2023 conference. We propose a fully automated algorithm based on deep encoder-decoder architecture. The main assumption behind our work is that data preprocessing and augmentation are much more important than the deep architecture, especially in low data regimes. Therefore, the solution is based on a variant of traditional convolutional U-Net. The proposed solution achieved a Dice score above 0.9 for all testing cases with the highest stability among all participants. The method scored 1st, 4th, and 3rd in terms of the clinical evaluation, quantitative results, and volumetric meshing quality, respectively. We freely release the source code, pretrained model, and provide access to the algorithm on the Grand-Challenge platform.Comment: MICCAI 2023 - SEG.A Challenge Contributio

Kinematics of concurrent vibratory rolling – screw system on the example of screen

The kinematics concurrent vibratory rolling screw system used in rolling screw screen that is used for sieving materials of fine and very fine grain was examined. The conducted experiments regarded the measurement of the torsional vibration sieve column (X and Y axis) and the measurement of the vertical vibration of the column (Z-axis)

Physiklehrerausbildung in Deutschland - Ergebnisse einer Umfrage

Im Jahr 2012 wurde im Rahmen einer von Ingolf Hertel und Siegfried Großmann initiierten DPG-Studie zur Lehrerausbildung eine Fragebogenerhebung zum gegenwärtigen Stand der Physiklehrerausbildung an den lehrerausbildenden Hochschulen in Deutschland durchgeführt. Gegenstand der Erhebung war neben der personellen Ausstattung vor allem die Frage der strukturellen und inhaltlichen Ausgestaltung des Studiums. Die Daten zeigen dass die Unterschiede im gymnasialen Lehramt deutlich geringer sind als im nicht-gymnasialen Lehramt, aber dennoch beachtlich sind: Der Beitrag gibt einen ersten Überblick über zentrale Ergebnisse. Eine Veröffentlichung der Gesamtauswertung ist für November 2014 vorgesehen

High-Resolution Cranial Defect Reconstruction by Iterative, Low-Resolution, Point Cloud Completion Transformers

Each year thousands of people suffer from various types of cranial injuries and require personalized implants whose manual design is expensive and time-consuming. Therefore, an automatic, dedicated system to increase the availability of personalized cranial reconstruction is highly desirable. The problem of the automatic cranial defect reconstruction can be formulated as the shape completion task and solved using dedicated deep networks. Currently, the most common approach is to use the volumetric representation and apply deep networks dedicated to image segmentation. However, this approach has several limitations and does not scale well into high-resolution volumes, nor takes into account the data sparsity. In our work, we reformulate the problem into a point cloud completion task. We propose an iterative, transformer-based method to reconstruct the cranial defect at any resolution while also being fast and resource-efficient during training and inference. We compare the proposed methods to the state-of-the-art volumetric approaches and show superior performance in terms of GPU memory consumption while maintaining high-quality of the reconstructed defects

Physiklehrerausbildung in Deutschland - Ergebnisse einer Umfrage

Im Jahr 2012 wurde im Rahmen einer von Ingolf Hertel und Siegfried Großmann initiierten DPG-Studie zur Lehrerausbildung eine Fragebogenerhebung zum gegenwärtigen Stand der Physiklehrerausbildung an den lehrerausbildenden Hochschulen in Deutschland durchgeführt. Gegenstand der Erhebung war neben der personellen Ausstattung vor allem die Frage der strukturellen und inhaltlichen Ausgestaltung des Studiums. Die Daten zeigen dass die Unterschiede im gymnasialen Lehramt deutlich geringer sind als im nicht-gymnasialen Lehramt, aber dennoch beachtlich sind: Der Beitrag gibt einen ersten Überblick über zentrale Ergebnisse. Eine Veröffentlichung der Gesamtauswertung ist für November 2014 vorgesehen