Virtual Reality opens up new possibilities as it allows to overcome real-life limitations and create novel experiences. While interacting with other people, it is beneficial to share a common view ...point. We modify the virtual world to allow face-to-face interaction with another person, while still retaining an optimal point of view on presented data. This is done by adapting the virtual environment independently for each user, using translation, rotation and scaling. The presented modification of the world gives a natural solution to the problems of collaborative analysis of content. It is therefore beneficial for usage in human-human interaction scenarios that support cooperative work.
Recently, Magnetic Resonance Fingerprinting (MRF) was proposed as a quantitative imaging technique for the simultaneous acquisition of tissue parameters such as relaxation times \(T_1\) and \(T_2\). ...Although the acquisition is highly accelerated, the state-of-the-art reconstruction suffers from long computation times: Template matching methods are used to find the most similar signal to the measured one by comparing it to pre-simulated signals of possible parameter combinations in a discretized dictionary. Deep learning approaches can overcome this limitation, by providing the direct mapping from the measured signal to the underlying parameters by one forward pass through a network. In this work, we propose a Recurrent Neural Network (RNN) architecture in combination with a novel quantile layer. RNNs are well suited for the processing of time-dependent signals and the quantile layer helps to overcome the noisy outliers by considering the spatial neighbors of the signal. We evaluate our approach using in-vivo data from multiple brain slices and several volunteers, running various experiments. We show that the RNN approach with small patches of complex-valued input signals in combination with a quantile layer outperforms other architectures, e.g. previously proposed CNNs for the MRF reconstruction reducing the error in \(T_1\) and \(T_2\) by more than 80%.
In the Editor's Choice 1 the development and demonstration of a highly efficient warm‐white all‐nitride phosphor‐converted light emitting diode (pc‐LED) is presented utilizing a GaN based quantum ...well blue LED and two novel nitrogen containing luminescent materials doped with Eu2+. These novel LEDs are superior to both incandescent and fluorescent lamps and may therefore become the next generation of general lighting sources.
The cover picture is an artist's view of the 2‐pc‐LED: On a copper slug and underneath a plastic lens a ‘flip‐chip’ is soldered to metal contacts; ‘flip‐chip’ meaning the substrate on which the stack of GaN and InGaN layers has been deposited is used as light exit, the (bottom) p‐contacts being highly reflective. The color converting phosphors are placed on top of the chip, embedded in silicone. Primary blue as well as color‐converted red and green photons are emitted.
The first author, Regina Mueller‐Mach, manages the Charac‐terization Laboratory at Lumileds which runs R&D work on phosphor converted LEDs in close cooperation with Philips Research Laboratories and the Department of Chemistry and Biochemistry of the University of Munich.
Deep-learning-based pipelines have shown the potential to revolutionalize microscopy image diagnostics by providing visual augmentations to a trained pathology expert. However, to match human ...performance, the methods rely on the availability of vast amounts of high-quality labeled data, which poses a significant challenge. To circumvent this, augmented labeling methods, also known as expert-algorithm-collaboration, have recently become popular. However, potential biases introduced by this operation mode and their effects for training neuronal networks are not entirely understood. This work aims to shed light on some of the effects by providing a case study for three pathologically relevant diagnostic settings. Ten trained pathology experts performed a labeling tasks first without and later with computer-generated augmentation. To investigate different biasing effects, we intentionally introduced errors to the augmentation. Furthermore, we developed a novel loss function which incorporates the experts' annotation consensus in the training of a deep learning classifier. In total, the pathology experts annotated 26,015 cells on 1,200 images in this novel annotation study. Backed by this extensive data set, we found that the consensus of multiple experts and the deep learning classifier accuracy, was significantly increased in the computer-aided setting, versus the unaided annotation. However, a significant percentage of the deliberately introduced false labels was not identified by the experts. Additionally, we showed that our loss function profited from multiple experts and outperformed conventional loss functions. At the same time, systematic errors did not lead to a deterioration of the trained classifier accuracy. Furthermore, a classifier trained with annotations from a single expert with computer-aided support can outperform the combined annotations from up to nine experts.
In all domains and sectors, the demand for intelligent systems to support the processing and generation of digital content is rapidly increasing. The availability of vast amounts of content and the ...pressure to publish new content quickly and in rapid succession requires faster, more efficient and smarter processing and generation methods. With a consortium of ten partners from research and industry and a broad range of expertise in AI, Machine Learning and Language Technologies, the QURATOR project, funded by the German Federal Ministry of Education and Research, develops a sustainable and innovative technology platform that provides services to support knowledge workers in various industries to address the challenges they face when curating digital content. The project's vision and ambition is to establish an ecosystem for content curation technologies that significantly pushes the current state of the art and transforms its region, the metropolitan area Berlin-Brandenburg, into a global centre of excellence for curation technologies.
We present time-resolved high energy x-ray diffraction (tr-HEXRD), time-resolved hard x-ray photoelectron spectroscopy (tr-HAXPES) and time-resolved grazing incidence small angle x-ray scattering ...(tr-GISAXS) data of the reactive molecular beam epitaxy (RMBE) of \(\mathrm{Fe_3O_4}\) ultrathin films on various substrates. Reciprocal space maps are recorded during the deposition of \(\mathrm{Fe_3O_4}\) on \(\mathrm{SrTiO_3(001)}\), MgO(001) and NiO/MgO(001) in order to observe the temporal evolution of Bragg reflections sensitive to the octahedral and tetrahedral sublattices of the inverse spinel structure of \(\mathrm{Fe_3O_4}\). A time delay between the appearance of rock salt and spinel-exclusive reflections reveals that first, the iron oxide film grows with \(\mathrm{Fe_{1-\delta}O}\) rock salt structure with exclusive occupation of octahedral lattice sites. When this film is 1.1\(\,\)nm thick, the further growth of the iron oxide film proceeds in the inverse spinel structure, with both octahedral and tetrahedral lattice sites being occupied. In addition, iron oxide on \(\mathrm{SrTiO_3(001)}\) initially grows with none of these structures. Here, the formation of the rock salt structure starts when the film is 1.5\(\,\)nm thick. This is confirmed by tr-HAXPES data obtained during growth of iron oxide on \(\mathrm{SrTiO_3(001)}\), which demonstrate an excess of \(\mathrm{Fe^{2+}}\) cations in growing films thinner than 3.2\(\,\)nm. This rock salt phase only appears during growth and vanishes after the supply of the Fe molecular beam is stopped. Thus, it can be concluded the rock salt structure of the interlayer is a property of the dynamic growth process. The tr-GISAXS data link these structural results to an island growth mode of the first 2-3\(\,\)nm on both MgO(001) and \(\mathrm{SrTiO_3(001)}\) substrates.
Abstract
The new layered oxonitridosilicate EuSi
2
O
2
N
2
has been synthesized in a radio‐frequency furnace at temperatures of about 1400 °C starting from europium(
III
) oxide (Eu
2
O
3
) and ...silicon diimide (Si(NH)
2
). The structure of the yellow material has been determined by single‐crystal X‐ray diffraction analysis (space group
P
1 (no. 1),
a
=709.5(1),
b
=724.6(1),
c
=725.6(1) pm,
α
=88.69(2),
β
=84.77(2),
γ
=75.84(2)°,
V
=360.19(9)×10
6
pm
3
,
Z
=4,
R
1=0.0631, 4551 independent reflections, 175 parameters). Its anionic Si
2
O
2
N
2
2−
layers consist of corner‐sharing SiON
3
tetrahedra with threefold connecting nitrogen and terminal oxygen atoms. High‐resolution transmission electron micrographs indicate both ordered and disordered crystallites as well as twinning. Magnetic susceptibility measurements of EuSi
2
O
2
N
2
exhibit Curie–Weiss behavior above 20 K with an effective magnetic moment of 7.80(5) μ
B
Eu
−1
, indicating divalent europium. Antiferromagnetic ordering is detected at 4.5(2) K. EuSi
2
O
2
N
2
shows a field‐induced transition with a critical field of 0.50(5) T. The four crystallographically different europium sites cannot be distinguished by
151
Eu Mössbauer spectroscopy. The room‐temperature spectrum is fitted by one signal at an isomer shift of
δ
=−12.3(1) mm s
−1
subject to quadrupole splitting of Δ
E
Q
=−2.3(1) mm s
−1
and an asymmetry parameter of 0.46(3). Luminescence measurements show a narrow emission band with regard to the four crystallographic europium sites with an emission maximum at
λ
=575 nm.
Das neue schichtartig aufgebaute Oxonitridosilicat EuSi
2
O
2
N
2
wurde in einem Hochfrequenzofen bei etwa 1400 °C aus Europium(
III
)‐oxid (Eu
2
O
3
) und Siliciumdiimid (Si(NH)
2
) hergestellt. Die Kristallstruktur der gelben Verbindung wurde mittels Einkristallröntgenstrukturanalyse bestimmt (Raumgruppe P1 (Nr. 1), a=709.5(1), b=724.6(1), c=725.6(1) pm, α=88.69(2), β=84.77(2), γ=75.84(2)°, V=360.19(9)⋅10
6
pm
3
, Z=4, R1=0.0631, 4551 unabhängige Reflexe, 175 Parameter). Die anionischen Si
2
O
2
N
2
2−
‐Schichten bestehen aus eckenverknüpften SiON
3
‐Tetraedern mit dreifach verbrückendem Stickstoff und terminalem Sauerstoff. Hochauflösende Transmissionselektronenmikroskopie (HRTEM) zeigt sowohl geordnete als auch ungeordnete Kristallite sowie Verzwillingung. Messungen der magnetischen Suszeptibilität von EuSi
2
O
2
N
2
ergeben oberhalb von 20 K Curie‐Weiss‐Verhalten mit einem effektiven magnetischen Moment von 7.80(5)
μ
B
Eu
−1
, welches auf zweiwertiges Europium hinweist. Bei 4.5(2) K wird antiferromagnetische Ordnung detektiert. EuSi
2
O
2
N
2
zeigt einen feldinduzierten Übergang mit einem kritischen Feld von 0.50(5) T. Die vier kristallographisch unterschiedlichen Europiumatome konnten durch
151
Eu‐Mößbauer‐Spektroskopie nicht unterschieden werden. Das Raumtemperaturspektrum konnte durch ein Signal bei einer Isomerenverschiebung von δ=−12.3(1) mm s
−1
gemäß einer Quadrupolaufspaltung von
Δ
E
Q
=−2.3(1) mm s
−1
und einem Asymmetrieparameter von 0.46(3) angepasst werden. Lumineszenzmessungen zeigten eine bzgl. der vier kristallographischen Europiumlagen schmale Emissionsbande mit einem Maximum bei λ=575 nm.
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