569 research outputs found
The Use of Sponge Iron in Electric Furnaces
Since autumn of 1971 sponge iron is used in the elec-tric furnace shop of Hamburger Stahlwerke GmbH for the steel making process. Both the equipment used for contin-uous charging of sponge iron and the melting practice applied is described. The effect of varying percentages of sponge iron in the charge on meltdown time and refining time, power consumption and further metallurgical aspects are reviewed
The Production of Sponge Iron Utilizing the Midland-Ross Process at Hamburger Stahlwerke GMBH
The Midland Ross direct reduction plant at Hamburger Stahlwerke is the third of its kind producing sponge iron since 1971. Economical and technological aspects of this new concept of a steel mill are studies. Concerning the direct reduction process particulars are given about plant installations, gas reforming, input materials, final product as well as first operational results
Dreidimensionaler Knochenabbau an Implantaten bei Patienten mit generalisierter aggressiver und chronischer Parodontitis
Ziel: Bestimmung des dreidimensionalen marginalen Knochenangebots an
Implantaten bei Patienten mit behandelter chronischer und aggressiver
Parodontitis 3 – 15 Jahre nach Belastung.
Material und Methode: Jeweils 17 Patienten mit generalisierter aggressiver
(GAP) und generalisierter chronischer Parodontitis (GCP) mit 119 Implantaten
wurden untersucht. Die Implantate wurden auf Knochenniveau inseriert und
hatten eine marginale Knochendicke von mindestens 2 mm. Die klinischen
Untersuchungen wurden innerhalb eines 3-monatigen Recalls nach
Eingliederung der Suprakonstruktion durchgeführt. DVT-Aufnahmen wurden zur
Bestimmung des dreidimensionalen Knochenverlusts und der Mukosadicke mit
einer Zinnfolie auf dem Weichgewebe einmalig nach 3-15 Jahren angefertigt.
Klinische Parameter wurden am selben Tag nochmals erhoben. Bei der
statistischen Auswertung wurde der Mann-Whitney-Test für Gruppenvergleiche
herangezogen und die Spearman Korrelation für den Zusammenhang zwischen
klinischen und radiologischen Parametern. Statistisch signifikant war p < 0,05.
Ergebnisse: Beide Gruppen hatten vestibulär den meisten Knochenabbau. Bei
GAP Patienten (4,49 ± 2,93 mm) war dies stärker ausgeprägt als bei GCP
Patienten (3,57 ± 2,94 mm). In beiden Gruppen zeigte sich der meiste
Knochenabbau im Unterkiefer (GAP: 3,03 ± 1,95 mm; GCP: 2,42 ± 0,97 mm).
Die periimplantäre Mukosa war im Oberkiefer (GAP: 1,94 ± 1,16 mm; GCP:
2,02 ± 1,14 mm) und im Unterkiefer (GAP: 1,02 ± 1,04 mm; GCP: 1,06 ± 0,96
mm) dick. Es zeigten sich signifikante Korrelationen zwischen den klinischen
Parametern und dem Knochenabbau im Unterkiefer von GAP Patienten.
Konklusion: Der größte Knochenabbau fand sich vestibulär in der anterioren
Mandibula. Bei GAP Patienten zeigten sich Korrelationen zwischen der
Mukosadicke und dem Knochenabbau. Plaque-bedingte Entzündungen sowie
die Breite und Dicke der KM schienen den größten Einfluss auf den
periimplantären Knochenabbau in unserer Studie gehabt zu haben
iPose: Instance-Aware 6D Pose Estimation of Partly Occluded Objects
We address the task of 6D pose estimation of known rigid objects from single
input images in scenarios where the objects are partly occluded. Recent
RGB-D-based methods are robust to moderate degrees of occlusion. For RGB
inputs, no previous method works well for partly occluded objects. Our main
contribution is to present the first deep learning-based system that estimates
accurate poses for partly occluded objects from RGB-D and RGB input. We achieve
this with a new instance-aware pipeline that decomposes 6D object pose
estimation into a sequence of simpler steps, where each step removes specific
aspects of the problem. The first step localizes all known objects in the image
using an instance segmentation network, and hence eliminates surrounding
clutter and occluders. The second step densely maps pixels to 3D object surface
positions, so called object coordinates, using an encoder-decoder network, and
hence eliminates object appearance. The third, and final, step predicts the 6D
pose using geometric optimization. We demonstrate that we significantly
outperform the state-of-the-art for pose estimation of partly occluded objects
for both RGB and RGB-D input
The History and Method of the Immanuel Movement and of Associated Groups
My interest in the subject of this thesis dates back ten years to the time when as a College and Theological Seminary Graduate I began to make my first visits to the sick in the congregation of which I had become pastor. Questions began to present themselves because the average sick calling seemed so perfunctory. Was I calling just to bring greetings from the church and to show my own interest? If I had prayer with the person who was sick, what answer should I expect to my prayer? Would or should there be immediate improvement and if not, why not? Would prayer help at all in the recovery? Was prayer merely a subjective spiritual exercise and if so did it have value alike for functional and organic sickness
Implicit 3D Orientation Learning for 6D Object Detection from RGB Images
We propose a real-time RGB-based pipeline for object detection and 6D pose
estimation. Our novel 3D orientation estimation is based on a variant of the
Denoising Autoencoder that is trained on simulated views of a 3D model using
Domain Randomization. This so-called Augmented Autoencoder has several
advantages over existing methods: It does not require real, pose-annotated
training data, generalizes to various test sensors and inherently handles
object and view symmetries. Instead of learning an explicit mapping from input
images to object poses, it provides an implicit representation of object
orientations defined by samples in a latent space. Our pipeline achieves
state-of-the-art performance on the T-LESS dataset both in the RGB and RGB-D
domain. We also evaluate on the LineMOD dataset where we can compete with other
synthetically trained approaches. We further increase performance by correcting
3D orientation estimates to account for perspective errors when the object
deviates from the image center and show extended results.Comment: Code available at: https://github.com/DLR-RM/AugmentedAutoencode
Ursinus College Bulletin Vol. 6, No. 6
A digitized copy of the March 1890 Ursinus College Bulletin.https://digitalcommons.ursinus.edu/ucbulletin/1054/thumbnail.jp
Kingella kingae expresses type IV pili that mediate adherence to respiratory epithelial and synovial cells
Kingella kingae is a gram-negative bacterium that colonizes the respiratory tract and is a common cause of septic arthritis and osteomyelitis. Despite the increasing frequency of K. kingae disease, little is known about the mechanism by which this organism adheres to respiratory epithelium and seeds joints and bones. Previous work showed that K. kingae expresses long surface fibers that vary in surface density. In the current study, we found that these fibers are type IV pili and are necessary for efficient adherence to respiratory epithelial and synovial cells and that the number of pili expressed by the bacterium correlates with the level of adherence to synovial cells but not with the level of adherence to respiratory cells. In addition, we established that the major pilin subunit is encoded by a pilA homolog in a conserved region of the chromosome that also contains a second pilin gene and a type IV pilus accessory gene, both of which are dispensable for pilus assembly and pilus-mediated adherence. Upon examination of the K. kingae genome, we identified two genes in physically separate locations on the chromosome that encode homologs of the Neisseria PilC proteins and that have only a low level homology to each other. Examination of mutant strains revealed that both of the K. kingae PilC homologs are essential for a wild-type level of adherence to both respiratory epithelial and synovial cells. Taken together, these results demonstrate that type IV pili and the two PilC homologs play important roles in mediating K. kingae adherence
Recovering 6D Object Pose: A Review and Multi-modal Analysis
A large number of studies analyse object detection and pose estimation at
visual level in 2D, discussing the effects of challenges such as occlusion,
clutter, texture, etc., on the performances of the methods, which work in the
context of RGB modality. Interpreting the depth data, the study in this paper
presents thorough multi-modal analyses. It discusses the above-mentioned
challenges for full 6D object pose estimation in RGB-D images comparing the
performances of several 6D detectors in order to answer the following
questions: What is the current position of the computer vision community for
maintaining "automation" in robotic manipulation? What next steps should the
community take for improving "autonomy" in robotics while handling objects? Our
findings include: (i) reasonably accurate results are obtained on
textured-objects at varying viewpoints with cluttered backgrounds. (ii) Heavy
existence of occlusion and clutter severely affects the detectors, and
similar-looking distractors is the biggest challenge in recovering instances'
6D. (iii) Template-based methods and random forest-based learning algorithms
underlie object detection and 6D pose estimation. Recent paradigm is to learn
deep discriminative feature representations and to adopt CNNs taking RGB images
as input. (iv) Depending on the availability of large-scale 6D annotated depth
datasets, feature representations can be learnt on these datasets, and then the
learnt representations can be customized for the 6D problem
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Uptake of 137Cs by Leafy Vegetables and Grains from Calcareous Soils
Cesium-137 was deposited on Bikini Island at Bikini Atoll in 1954 as a result of nuclear testing and has been transported and cycled in the ecosystem ever since. Atoll soils are of marine origin and are almost pure CaCO{sub 3} with high concentrations of organic matter in the top 40 cm. Data from previous experiments with mature fruit trees show very high transfer factors (TF's), [Bq g{sup -1} plant/ Bq g{sup -1} soil, both in dry weight] into fruits from atoll calcareous soil. These TF's are much higher than reported for continental, silica-based soils. In this report TF's for 5 types of leafy vegetable crops and 2 types of grain crops are provided for use in predictive dose assessments and for comparison with other data from other investigators working with other types of soil in the IAEA CRP ''The Classification of Soil Systems on the Basis of Transfer Factors of Radionuclides from Soil to Reference Plants''. Transfer factors for plants grown on calcareous soil are again very high relative to clay-containing soils and range from 23 to 39 for grain crops and 21 to 113 for leafy vegetables. Results from these experiments, in this unique, high pH, high organic content, low potassium (K) soil, provide a boundary condition for models relating soil properties to TF
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