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

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