Hyperfine characterization and coherence lifetime extension in Pr3+:La2(WO4)3

Rare-earth ions in dielectric crystals are interesting candidates for storing quantum states of photons. A limiting factor on the optical density and thus the conversion efficiency is the distortion introduced in the crystal by doping elements of one type into a crystal matrix of another type. Here, we investigate the system Pr3+:La2(WO4)3, where the similarity of the ionic radii of Pr and La minimizes distortions due to doping. We characterize the praseodymium hyperfine interaction of the ground state (3H4) and one excited state (1D2) and determine the spin Hamiltonian parameters by numerical analysis of Raman-heterodyne spectra, which were collected for a range of static external magnetic field strengths and orientations. On the basis of a crystal field analysis, we discuss the physical origin of the experimentally determined quadrupole and Zeeman tensor characteristics. We show the potential for quantum memory applications by measuring the spin coherence lifetime in a magnetic field that is chosen such that additional magnetic fields do not shift the transition frequency in first order. Experimental results demonstrate a spin coherence lifetime of 158 ms - almost three orders of magnitude longer than in zero field.Comment: 14 pages, 6 figure

The cost of infidelity to female reed buntings

Females of many socially monogamous bird species accept or even actively seek copulations outside the social pair bond. It has been shown that females profit from extrapair fertilization by increased offspring quality, but extrapair mating may also induce costs to females. We measured parental food provisioning and paternity in the reed bunting, Emberiza schoeniclus, a species with biparental brood care and high levels of extrapair paternity (EPP). We found a negative relationship between the proportion of EPP in broods and paternal care across the local population. Individual males adjusted food provisioning to the amount of EPP between sequential broods. Females did compensate for low male food provisioning. The cost of extrapair fertilizations to females is increased nestling mortality due to the social partner's reduction of brood care. If the mixed mating system of the reed bunting is at an evolutionary equilibrium, we expect that genetic fitness for males as well as for females is maximized. Any costs incurred by extrapair mating should therefore not exceed the benefits for both sexe

PyRaDiSe: A Python package for DICOM-RT-based auto-segmentation pipeline construction and DICOM-RT data conversion.

BACKGROUND AND OBJECTIVE Despite fast evolution cycles in deep learning methodologies for medical imaging in radiotherapy, auto-segmentation solutions rarely run in clinics due to the lack of open-source frameworks feasible for processing DICOM RT Structure Sets. Besides this shortage, available open-source DICOM RT Structure Set converters rely exclusively on 2D reconstruction approaches leading to pixelated contours with potentially low acceptance by healthcare professionals. PyRaDiSe, an open-source, deep learning framework independent Python package, addresses these issues by providing a framework for building auto-segmentation solutions feasible to operate directly on DICOM data. In addition, PyRaDiSe provides profound DICOM RT Structure Set conversion and processing capabilities; thus, it applies also to auto-segmentation-related tasks, such as dataset construction for deep learning model training. METHODS The PyRaDiSe package follows a holistic approach and provides DICOM data handling, deep learning model inference, pre-processing, and post-processing functionalities. The DICOM data handling allows for highly automated and flexible handling of DICOM image series, DICOM RT Structure Sets, and DICOM registrations, including 2D-based and 3D-based conversion from and to DICOM RT Structure Sets. For deep learning model inference, extending given skeleton classes is straightforwardly achieved, allowing for employing any deep learning framework. Furthermore, a profound set of pre-processing and post-processing routines is included that incorporate partial invertibility for restoring spatial properties, such as image origin or orientation. RESULTS The PyRaDiSe package, characterized by its flexibility and automated routines, allows for fast deployment and prototyping, reducing efforts for auto-segmentation pipeline implementation. Furthermore, while deep learning model inference is independent of the deep learning framework, it can easily be integrated into famous deep learning frameworks such as PyTorch or Tensorflow. The developed package has successfully demonstrated its capabilities in a research project at our institution for organs-at-risk segmentation in brain tumor patients. Furthermore, PyRaDiSe has shown its conversion performance for dataset construction. CONCLUSIONS The PyRaDiSe package closes the gap between data science and clinical radiotherapy by enabling deep learning segmentation models to be easily transferred into clinical research practice. PyRaDiSe is available on https://github.com/ubern-mia/pyradise and can be installed directly from the Python Package Index using pip install pyradise

Effects of pre-pandemic school improvement and digital learning on schools during the COVID-19 pandemic

After the outbreak of the COVID-19 pandemic, schools had to continuously adapt to new pandemic-related regulations and challenges, including the ad hoc transition to remote learning. According to theories on school improvement and professionalisation, sharing knowledge and experiences with digital learning is helpful when dealing with related issues. However, no existing empirical studies analyse longitudinally how pre-pandemic experiences with sharing knowledge and digital learning impacted perceived professionalisation during the pandemic and how this relationship is mediated both by schools’ strategies to improve learning and by schools’ collective efficacy. For this study N = 280 school principals from Germany, Austria, and German-speaking Swiss cantons participated in two online questionnaires in 2020 and 2021. Results from the structural equation model reveal that schools’ pre-pandemic experiences with knowledge sharing and digital learning are positively indirectly related to the schools’ perceived professionalisation in the first and second year of the pandemic. The relationship is mediated by the schools’ collective efficacy in dealing with the pandemic and the schools’ use of strategies to improve teaching. The results highlight the importance of building school improvement capacity and supporting schools in digital learning to navigate through unexpected emergencies like a pandemic

AtPTR4 and AtPTR6 are differentially expressed, tonoplast-localized members of the peptide transporter/nitrate transporter 1 (PTR/NRT1) family

Members of the peptide transporter/nitrate transporter 1 (PTR/NRT1) family in plants transport a variety of substrates like nitrate, di- and tripepetides, auxin and carboxylates. We isolated two members of this family from Arabidopsis, AtPTR4 and AtPTR6, which are highly homologous to the characterized di- and tripeptide transporters AtPTR1, AtPTR2 and AtPTR5. All known substrates of members of the PTR/NRT1 family were tested using heterologous expression in Saccharomyces cerevisiae mutants and oocytes of Xenopus laevis, but none could be identified as substrate of AtPTR4 or AtPTR6. AtPTR4 and AtPTR6 show distinct expression patterns, while AtPTR4 is expressed in the vasculature of the plants, AtPTR6 is highly expressed in pollen and during senescence. Phylogenetic analyses revealed that AtPTR2, 4 and 6 belong to one clade of subgoup II, whereas AtPTR1 and 5 are found in a second clade. Like AtPTR2, AtPTR4-GFP and AtPTR6-GFP fusion proteins are localized at the tonoplast. Vacuolar localization was corroborated by co-localization of AtPTR2-YFP with the tonoplast marker protein GFP-AtTIP2;1 and AtTIP1;1-GFP. This indicates that the two clades reflect different intracellular localization at the tonoplast (AtPTR2, 4, 6) and plasma membrane (AtPTR1, 5), respectivel

Walking and running with non-specific chronic low back pain: what about the lumbar lordosis angle?

Non-specific chronic low back pain (NSCLBP) is a major health problem, affecting about one fifth of the population worldwide. To avoid further pain or injury, patients with NSCLBP seem to adopt a stiffer movement pattern during everyday living activities. However, it remains unknown how NSCLBP affects the lumbar lordosis angle (LLA) during repetitive activities such as walking or running. This pilot study therefore aimed at exploring possible NSCLBP-related alterations in LLAs during walking and running by focusing on discrete parameters as well as continuous data. Thirteen patients with NSCLBP and 20 healthy pain-free controls were enrolled and underwent a full-body movement analysis involving various everyday living activities such as standing, walking and running. LLAs were derived from markers placed on the spinous processes of the vertebrae L1-L5 and S1. Possible group differences in discrete (average and range of motion (ROM)) and continuous LLAs were analyzed descriptively using mean differences with confidence intervals ranging from 95% to 75%. Patients with NSCLBP indicated reduced average LLAs during standing, walking and running and a tendency for lower LLA-ROM during walking. Analyses of continuous data indicated the largest group differences occurring around 25% and 70% of the walking and 25% and 75% of the running cycle. Furthermore, patients indicated a reversed movement pattern during running, with increasing instead of a decreasing LLAs after foot strike. This study provides preliminary evidence that NSCLBP might affect LLAs during walking and running. These results can be used as a basis for future large-scale investigations involving hypothesis testing.Comment: This is the accepted manuscript version of an article published in the Journal of Biomechanics (https://doi.org/10.1016/j.jbiomech.2020.109883

Fear avoidance beliefs are associated with reduced lumbar spine flexion during object lifting in pain-free adults

There is a long-held belief that physical activities such as lifting with a flexed spine is generally harmful for the back and can cause low back pain (LBP), potentially reinforcing fear avoidance beliefs underlying pain-related fear. In chronic LBP patients, pain-related fear has been shown to be associated with reduced lumbar range of motion during lifting, suggesting a protective response to pain. However, despite short term beneficial effects for tissue health, recent evidence suggests that maintaining a protective trunk movement strategy may also pose a risk for (persistent) LBP due to possible pro-nociceptive consequences of altered spinal motion, potentially leading to increased loading on lumbar tissues. Yet, it is unknown if similar protective movement strategies already exist in pain-free individuals which would yield potential insights into the role of fear avoidance beliefs in motor behavior in the absence of pain. Therefore, the aim of this study is to test whether fear avoidance beliefs influence spinal motion during lifting in a healthy cohort of pain-free adults without a history of chronic pain. The study subjects (N=57) filled out several pain-related fear questionnaires and were asked to perform a lifting task (5kg-box). High-resolution spinal kinematics were assessed using an optical motion capturing system. Time-sensitive analyses were performed based on statistical parametric mapping. The results demonstrated time-specific and negative relationships between self-report measures of pain-related fear and lumbar spine flexion angles during lifting, indicating potential unfavorable interactions between psychological factors and spinal motion during lifting in pain-free subjects