Helicity sensitive terahertz radiation detection by dual-grating-gate high electron mobility transistors

We report on the observation of a radiation helicity sensitive photocurrent excited by terahertz (THz) radiation in dual-grating-gate (DGG) InAlAs/InGaAs/InAlAs/InP high electron mobility transistors (HEMT). For a circular polarization the current measured between source and drain contacts changes its sign with the inversion of the radiation helicity. For elliptically polarized radiation the total current is described by superposition of the Stokes parameters with different weights. Moreover, by variation of gate voltages applied to individual gratings the photocurrent can be defined either by the Stokes parameter defining the radiation helicity or those for linear polarization. We show that artificial non-centrosymmetric microperiodic structures with a two-dimensional electron system excited by THz radiation exhibit a dc photocurrent caused by the combined action of a spatially periodic in-plane potential and spatially modulated light. The results provide a proof of principle for the application of DGG HEMT for all-electric detection of the radiation's polarization state.Comment: 7 pages, 4 figure

Improving Semantic Segmentation of Roof Segments Using Large-Scale Datasets Derived from 3D City Models and High-Resolution Aerial Imagery

Advances in deep learning techniques for remote sensing as well as the increased availability of high-resolution data enable the extraction of more detailed information from aerial images. One promising task is the semantic segmentation of roof segments and their orientation. However, the lack of annotated data is a major barrier for deploying respective models on a large scale. Previous research demonstrated the viability of the deep learning approach for the task, but currently, published datasets are small-scale, manually labeled, and rare. Therefore, this paper extends the state of the art by presenting a novel method for the automated generation of large-scale datasets based on semantic 3D city models. Furthermore, we train a model on a dataset 50 times larger than existing datasets and achieve superior performance while applying it to a wider variety of buildings. We evaluate the approach by comparing networks trained on four dataset configurations, including an existing dataset and our novel large-scale dataset. The results show that the network performance measured as intersection over union can be increased from 0.60 for the existing dataset to 0.70 when the large-scale model is applied on the same region. The large-scale model performs superiorly even when applied to more diverse test samples, achieving 0.635. The novel approach contributes to solving the dataset bottleneck and consequently to improving semantic segmentation of roof segments. The resulting remotely sensed information is crucial for applications such as solar potential analysis or urban planning

Deep brain stimulation: Connectivity profile for bradykinesia alleviation

Objective Subthalamic deep brain stimulation may alleviate bradykinesia in Parkinson patients. Research suggests that this stimulation effect may be mediated by brain networks like the corticocerebellar loop. This study investigated the connectivity between stimulation sites and cortical and subcortical structures to identify connections for effective stimulation. Methods We retrospectively investigated 21 patients with Parkinson disease with bilateral subthalamic deep brain stimulation. Stimulation effectiveness in reducing bradykinesia, tremor, and rigidity was evaluated for each electrode contact in brain hemispheres contralateral to the affected hemibody. Dysarthric side effects were also examined. Probabilistic tractography based on diffusion-weighted imaging was performed in individual patient-specific brains using electrode contacts as seeds. Connectivity profiles of contacts with effective and noneffective stimulation were compared. Results Connectivity profiles of effective and noneffective contacts differed. Moreover, the connectivity profile for bradykinesia differed from that for rigidity, tremor, or dysarthria. Regarding bradykinesia, effective contacts were significantly more often connected with the ipsilateral superior cerebellar peduncle and the ipsilateral dentate nucleus, which correspond to the ipsilateral portion of the cerebellothalamocortical pathway. Rigidity was mitigated by stimulation of ascending brainstem and intralaminar thalamic connections. Tremor alleviation was related to connections with the internal capsule (anterior limb) and the pallidum. Dysarthric side effects were associated with connections to the supplementary motor area and the decussating cerebellothalamocortical pathway. Interpretation Whereas bradykinesia seems to be mitigated by stimulation of the ascending, ipsilateral cerebellothalamocortical pathway, stimulation of the descending corticopontocerebellar pathway may be ineffective. Rigidity, tremor, and dysarthric side effects seem to be influenced by different neural networks. ANN NEUROL 2019;85:852-864

Statewide Impact of the COVID Pandemic on Pediatric Appendicitis in California: A Multicenter Study.

BackgroundThe COVID-19 pandemic has resulted in delays in presentation for other urgent medical conditions, including pediatric appendicitis. Several single-center studies have reported worse outcomes, but no state-level data is available. We aimed to determine the statewide effect of the COVID-19 pandemic on the presentation and management of pediatric appendicitis patients.Materials and methodsPatients < 18 years old with acute appendicitis at four tertiary pediatric hospitals in California between March 19, 2020 to September 19, 2020 (COVID-era) were compared to a pre-COVID cohort (March 19, 2019 to September 19, 2019). The primary outcome was the rate of perforated appendicitis. Secondary outcomes were symptom duration prior to presentation, and rates of non-operative management.ResultsRates of perforated appendicitis were unchanged (40.4% of 592 patients pre-COVID versus 42.1% of 606 patients COVID-era, P = 0.17). The median symptom duration was 2 days in both cohorts (P = 0.90). Computed tomography (CT) use rose from 39.8% pre-COVID to 49.4% during COVID (P = 0.002). Non-operative management increased during the pandemic (8.8% pre-COVID versus 16.2% COVID-era, P < 0.0001). Hospital length of stay (LOS) was longer (2 days pre-COVID versus 3 days during COVID, P < 0.0001).ConclusionsPediatric perforated appendicitis rates did not rise during the first six months of the COVID-19 pandemic in California in this multicenter study, and there were no delays in presentation noted. There was a higher rate of CT scans, non-operative management, and longer hospital lengths of stay

Probabilistic vs. deterministic fiber tracking and the influence of different seed regions to delineate cerebellar-thalamic fibers in deep brain stimulation

This study compared tractography approaches for identifying cerebellar-thalamic fiber bundles relevant to planning target sites for deep brain stimulation (DBS). In particular, probabilistic and deterministic tracking of the dentate-rubro-thalamic tract (DRTT) and differences between the spatial courses of the DRTT and the cerebello-thalamo-cortical (CTC) tract were compared. Six patients with movement disorders were examined by magnetic resonance imaging (MRI), including two sets of diffusion-weighted images (12 and 64 directions). Probabilistic and deterministic tractography was applied on each diffusion-weighted dataset to delineate the DRTT. Results were compared with regard to their sensitivity in revealing the DRTT and additional fiber tracts and processing time. Two sets of regions-of-interests (ROIs) guided deterministic tractography of the DRTT or the CTC, respectively. Tract distances to an atlas-based reference target were compared. Probabilistic fiber tracking with 64 orientations detected the DRTT in all twelve hemispheres. Deterministic tracking detected the DRTT in nine (12 directions) and in only two (64 directions) hemispheres. Probabilistic tracking was more sensitive in detecting additional fibers (e.g. ansa lenticularis and medial forebrain bundle) than deterministic tracking. Probabilistic tracking lasted substantially longer than deterministic. Deterministic tracking was more sensitive in detecting the CTC than the DRTT. CTC tracts were located adjacent but consistently more posterior to DRTT tracts. These results suggest that probabilistic tracking is more sensitive and robust in detecting the DRTT but harder to implement than deterministic approaches. Although sensitivity of deterministic tracking is higher for the CTC than the DRTT, targets for DBS based on these tracts likely differ