Prostate Cancer Nodal Staging: Using Deep Learning to Predict 68Ga-PSMA-Positivity from CT Imaging Alone

Lymphatic spread determines treatment decisions in prostate cancer (PCa) patients. 68Ga-PSMA-PET/CT can be performed, although cost remains high and availability is limited. Therefore, computed tomography (CT) continues to be the most used modality for PCa staging. We assessed if convolutional neural networks (CNNs) can be trained to determine 68Ga-PSMA-PET/CT-lymph node status from CT alone. In 549 patients with 68Ga-PSMA PET/CT imaging, 2616 lymph nodes were segmented. Using PET as a reference standard, three CNNs were trained. Training sets balanced for infiltration status, lymph node location and additionally, masked images, were used for training. CNNs were evaluated using a separate test set and performance was compared to radiologists' assessments and random forest classifiers. Heatmaps maps were used to identify the performance determining image regions. The CNNs performed with an Area-Under-the-Curve of 0.95 (status balanced) and 0.86 (location balanced, masked), compared to an AUC of 0.81 of experienced radiologists. Interestingly, CNNs used anatomical surroundings to increase their performance, "learning" the infiltration probabilities of anatomical locations. In conclusion, CNNs have the potential to build a well performing CT-based biomarker for lymph node metastases in PCa, with different types of class balancing strongly affecting CNN performance

Battery-Electric Powertrain System Design for the HorizonUAM Multirotor Air Taxi Concept

The work presented herein has been conducted within the DLR internal research project HorizonUAM, which encompasses research within numerous areas related to urban air mobility. One of the project goals was to develop a safe and certifiable onboard system concept. This paper aims to present the conceptual propulsion system architecture design for an all-electric battery-powered multirotor electric Vertical Takeoff and Landing (eVTOL) vehicle. Therefore, a conceptual design method was developed that provides a structured approach for designing the safe multirotor propulsion architecture. Based on the concept of operation the powertrain system was initially predefined, iteratively refined based on the safety assessment and validated through component sizing and simulations. The analysis was conducted within three system groups that were developed in parallel: the drivetrain, the energy supply and the thermal management system. The design process indicated that a pure quadcopter propulsion system can merely be designed reasonably for meeting the European Union Aviation Safety Agency (EASA) reliability specifications. By adding two push propellers and implementing numerous safety as well as passivation measures the reliability specifications defined by EASA could finally be fulfilled. The subsequent system simulations also verified that the system architecture is capable of meeting the requirements of the vehicle concept of operations. However, further work is required to extend the safety analysis to additional system components as the thermal management system or the battery management system and to reduce propulsion system weight.Comment: 38 pages, 27 figures, CEAS Aeronautical Journal Special Issue "HorizonUAM - Opportunities and Challenges of Urban Air Mobility

Theoretical study of the (3x2) reconstruction of beta-SiC(001)

By means of ab initio molecular dynamics and band structure calculations, as well as using calculated STM images, we have singled out one structural model for the (3x2) reconstruction of the Si-terminated (001) surface of cubic SiC, amongst several proposed in the literature. This is an alternate dimer-row model, with an excess Si coverage of 1/3, yielding STM images in good accord with recent measurements [F.Semond et al. Phys. Rev. Lett. 77, 2013 (1996)].Comment: To be published in PRB Rapid. Com

Distributed Caching for Processing Raw Arrays

As applications continue to generate multi-dimensional data at exponentially increasing rates, fast analytics to extract meaningful results is becoming extremely important. The database community has developed array databases that alleviate this problem through a series of techniques. In-situ mechanisms provide direct access to raw data in the original format---without loading and partitioning. Parallel processing scales to the largest datasets. In-memory caching reduces latency when the same data are accessed across a workload of queries. However, we are not aware of any work on distributed caching of multi-dimensional raw arrays. In this paper, we introduce a distributed framework for cost-based caching of multi-dimensional arrays in native format. Given a set of files that contain portions of an array and an online query workload, the framework computes an effective caching plan in two stages. First, the plan identifies the cells to be cached locally from each of the input files by continuously refining an evolving R-tree index. In the second stage, an optimal assignment of cells to nodes that collocates dependent cells in order to minimize the overall data transfer is determined. We design cache eviction and placement heuristic algorithms that consider the historical query workload. A thorough experimental evaluation over two real datasets in three file formats confirms the superiority - by as much as two orders of magnitude - of the proposed framework over existing techniques in terms of cache overhead and workload execution time

Modeling the series of (n x 2) Si-rich reconstructions of beta-SiC(001): a prospective atomic wire?

We perform ab initio plane wave supercell density functional calculations on three candidate models of the (3 x 2) reconstruction of the beta-SiC(001) surface. We find that the two-adlayer asymmetric-dimer model (TAADM) is unambiguously favored for all reasonable values of Si chemical potential. We then use structures derived from the TAADM parent to model the silicon lines that are observed when the (3 x 2) reconstruction is annealed (the (n x 2) series of reconstructions), using a tight-binding method. We find that as we increase n, and so separate the lines, a structural transition occurs in which the top addimer of the line flattens. We also find that associated with the separation of the lines is a large decrease in the HOMO-LUMO gap, and that the HOMO state becomes quasi-one-dimensional. These properties are qualititatively and quantitatively different from the electronic properties of the original (3 x 2) reconstruction.Comment: 22 pages, including 6 EPS figure

Difficult to control atopic dermatitis

Difficult to control atopic dermatitis (AD) presents a therapeutic challenge and often requires combinations of topical and systemic treatment. Anti-inflammatory treatment of severe AD most commonly includes topical glucocorticosteroids and topical calcineurin antagonists used for exacerbation management and more recently for proactive therapy in selected cases. Topical corticosteroids remain the mainstay of therapy, the topical calcineurin inhibitors tacrolimus and pimecrolimus are preferred in certain locations. Systemic anti-inflammatory treatment is an option for severe refractory cases. Microbial colonization and superinfection contribute to disease exacerbation and thus justify additional antimicrobial/antiseptic treatment. Systemic antihistamines (H1) may relieve pruritus but do not have sufficient effect on eczema. Adjuvant therapy includes UV irradiation preferably of UVA1 wavelength. "Eczema school" educational programs have been proven to be helpful

A rigidity property of asymptotically simple spacetimes arising from conformally flat data

Given a time symmetric initial data set for the vacuum Einstein field equations which is conformally flat near infinity, it is shown that the solutions to the regular finite initial value problem at spatial infinity extend smoothly through the critical sets where null infinity touches spatial infinity if and only if the initial data coincides with Schwarzschild data near infinity.Comment: 37 page

A first assessment of the impact of the extreme 2018 summer drought on Central European forests

In 2018, Central Europe experienced one of the most severe and long-lasting summer drought and heat wave ever recorded. Before 2018, the 2003 millennial drought was often invoked as the example of a “hotter drought”, and was classified as the most severe event in Europe for the last 500 years. First insights now confirm that the 2018 drought event was climatically more extreme and had a greater impact on forest ecosystems of Austria, Germany and Switzerland than the 2003 drought. Across this region, mean growing season air temperature from April to October was more than 3.3°C above the long-term average, and 1.2°C warmer than in 2003. Here, we present a first impact assessment of the severe 2018 summer drought and heatwave on Central European forests. In response to the 2018 event, most ecologically and economically important tree species in temperate forests of Austria, Germany and Switzerland showed severe signs of drought stress. These symptoms included exceptionally low foliar water potentials crossing the threshold for xylem hydraulic failure in many species and observations of widespread leaf discoloration and premature leaf shedding. As a result of the extreme drought stress, the 2018 event caused unprecedented drought-induced tree mortality in many species throughout the region. Moreover, unexpectedly strong drought-legacy effects were detected in 2019. This implies that the physiological recovery of trees was impaired after the 2018 drought event, leaving them highly vulnerable to secondary drought impacts such as insect or fungal pathogen attacks. As a consequence, mortality of trees triggered by the 2018 events is likely to continue for several years. Our assessment indicates that many common temperate European forest tree species are more vulnerable to extreme summer drought and heat waves than previously thought. As drought and heat events are likely to occur more frequently with the progression of climate change, temperate European forests might approach the point for a substantial ecological and economic transition. Our assessment also highlights the urgent need for a pan-European ground-based monitoring network suited to track individual tree mortality, supported by remote sensing products with high spatial and temporal resolution to track, analyse and forecast these transitions

Overcoming the blood–brain barrier: the role of nanomaterials in treating neurological diseases

Therapies directed toward the central nervous system remain difficult to translate into improved clinical outcomes. This is largely due to the blood–brain barrier (BBB), arguably the most tightly regulated interface in the human body, which routinely excludes most therapeutics. Advances in the engineering of nanomaterials and their application in biomedicine (i.e., nanomedicine) are enabling new strategies that have the potential to help improve our understanding and treatment of neurological diseases. Herein, the various mechanisms by which therapeutics can be delivered to the brain are examined and key challenges facing translation of this research from benchtop to bedside are highlighted. Following a contextual overview of the BBB anatomy and physiology in both healthy and diseased states, relevant therapeutic strategies for bypassing and crossing the BBB are discussed. The focus here is especially on nanomaterial‐based drug delivery systems and the potential of these to overcome the biological challenges imposed by the BBB. Finally, disease‐targeting strategies and clearance mechanisms are explored. The objective is to provide the diverse range of researchers active in the field (e.g., material scientists, chemists, engineers, neuroscientists, and clinicians) with an easily accessible guide to the key opportunities and challenges currently facing the nanomaterial‐mediated treatment of neurological diseases