Investigation of air solubility in jet A fuel at high pressures

The solubility and density properties of saturated mixtures of fuels and gases were measured. The fuels consisted of Jet A and dodecane, the gases were air and nitrogen. The test range included pressures of 1.03 to 10.34 MPa and temperatures of 298 to 373 K. The results were correlated successfully, using the Soave equation of state. Over this test range, dissolved gas concentrations were roughly proportional to pressure and increased slightly with increasing temperature. Mixture density was relatively independent of dissolved gas concentration

Deutschsprachige und bilinguale Studiengänge : eine Chance für Deutsch als Fremdsprache in Russland

Der Bericht der Ständigen Arbeitsgruppe Deutsch als Fremdsprache (2006) für das Jahr 2005 zeigt, dass Russland, trotz eines Rückgangs der Lernerzahlen, immer noch das Land mit den meisten Deutschlernern (mehr als 3,3 Millionen) und mit dem größten Deutschlernangebot an den Schulen und den Universitäten (ca. 1000 Hochschulen) ist. Bei einer Umfrage unter 1025 Personen in den Städten Jakutsk, Kaliningrad, Moskau, Saratov und St. Petersburg waren 100 % der Befragten der Meinung, dass Englisch für die beruflichen Aussichten die wichtigste Sprache sei, aber 89 % schätzten die Kenntnis des Deutschen für ebenso wichtig ein und 95 % waren sogar der Meinung, dass durch ein sehr gutes Erlernen der deutschen Sprache im bilingualen Unterricht an Schulen sich die Berufschancen der Lerner erheblich verbessern (vgl. Baur 2005)

Can research, development and innovation extend the life of the PGM Mining Industry

Abstract: Some recent public reports have warned that South African Platinum Group Metals (PGMs) Mineral Reserves based on conventional drill and blast technologies will be depleted by 2030 and Mineral Reserves supported by mechanised mining methods exhausted by 2035 (Turner 2016). The South African mining industry is currently considering research and development as a means to find more efficient, modern and cost effective ways to mine. The mineral industry looks to mechanisation, non-explosive rock breaking, automation, and continuous mining as the panacea for its problems with the goal that results from Research and Development activities will be capable of extending PGM Mineral Reserves beyond 2042..

The valuation of an exploration project having inferred resources

Abstract: Mineral Asset valuation of Mineral Resources and Mineral Reserves as the single fundamental asset for a mining company, according to the SAMVAL Code, CIMVAL Code or the VALMIN code, can be carried out using three valuation approaches, namely; the Cash Flow (Income) Approach, Market Approach, and Cost Approach. Under the 2009 SAMVAL Code the Market and Cost approaches are viewed as the preferred approaches to the valuation of Exploration Properties with mainly only Inferred Mineral Resources, with the Cash Flow Approach ’not generally used’. The updated 2016 SAMVAL Code has split Exploration Properties into two categories; early stage and advanced stage Exploration Properties. For both stages of Exploration Properties the Market and Cost Approach is ‘widely used’, while the Income Approach is ’not generally used’ for early stage Exploration Properties and ’less widely used’ for advanced stage Exploration Properties. In both versions of the SAMVAL Code the Income Approach is the least preferred method for valuations of exploration projects, with only Mineral Resources and without any credible studies to assess the technical and economic viability. Under the 2016 SAMVAL Code, an advanced Exploration Property is defined as a project that has undertaken considerable exploration and a Mineral Resource estimate has been defined and a Scoping Study has been applied to determine whether there are reasonable prospects for eventual economic extraction. This paper looks at the valuation of early Exploration Properties, especially those with mainly Inferred Mineral Resources, with particular attention on the use of the Income Approach. It will discuss circumstances where Inferred Mineral Resources could be or should not be valued using in the Income Approach-based valuation methodologies

Wie kommen wir an die Bilder in unseren Köpfen? Zur Methodologie einer interkulturell anwendbaren Stereotypenerhebung

SI.DE is an international research project at the University of Duisburg-Essen, which examines German, Russian, Turkish and Chinese auto- and heterostereotypes. Questioning for the study is made online and consists of two surveys; one survey based on stereotypes and a second based on the perception of each other’s foreign language. The questionnaire on stereotypes contains 140 attributes in total, while the respondents can select all of them without any limitation. The choice of these attributes is based on previous investigations, where methodologically formative surveys within the field of stereotype research had been compared with each other. Therefore, it is of high importance to take account of the transferability of the attributes to other languages, without any loss of crop-specific connotations. After the first phase of the study, the items on the attribute list have proved valuable. The construction of the questionnaire and the selected items are described in the following. Moreover, the perception in each other’s language is being researched on the basis of polarity profiles

Viewset Diffusion: (0-)image-conditioned 3D generative models from 2D data

We present Viewset Diffusion, a diffusion-based generator that outputs 3D objects while only using multi-view 2D data for supervision. We note that there exists a one-to-one mapping between viewsets, i.e., collections of several 2D views of an object, and 3D models. Hence, we train a diffusion model to generate viewsets, but design the neural network generator to reconstruct internally corresponding 3D models, thus generating those too. We fit a diffusion model to a large number of viewsets for a given category of objects. The resulting generator can be conditioned on zero, one or more input views. Conditioned on a single view, it performs 3D reconstruction accounting for the ambiguity of the task and allowing to sample multiple solutions compatible with the input. The model performs reconstruction efficiently, in a feed-forward manner, and is trained using only rendering losses using as few as three views per viewset. Project page: szymanowiczs.github.io/viewset-diffusion

Unsupervised learning of probably symmetric deformable 3D objects from images in the wild (extended abstract)

We propose a method to learn 3D deformable object categories from raw single-view images, without external supervision. The method is based on an autoencoder that factors each input image into depth, albedo, viewpoint and illumination. In order to disentangle these components without supervision, we use the fact that many object categories have, at least approximately, a symmetric structure. We show that reasoning about illumination allows us to exploit the underlying object symmetry even if the appearance is not symmetric due to shading. Furthermore, we model objects that are probably, but not certainly, symmetric by predicting a symmetry probability map, learned end-to-end with the other components of the model. Our experiments show that this method can recover very accurately the 3D shape of human faces, cat faces and cars from single-view images, without any supervision or a prior shape model. Code and demo available at https://github.com/elliottwu/unsup3d