The extraction of wheat germs,milkweed seeds,and cottonseed by trichloroethylene

Summary Specific gravity-concentration data have been determined for wheat germ oil, milkweed seed oil, and cottonseed oil miscellas where trichloroethylene is used as a solvent. Extraction rate data at two temperatures and pilot plant runs on wheat germs, cottonseed, cottonseed meats, and milkweed seeds indicate increasing extraction time in the order given.     

Electrooxidation of CO and CO/H2 mixtures on a Pt-Sn catalyst prepared by an implantation method

A new type of ion implantation technique is used to create a non-equilibrium Pt-Sn(IMP) near-surface alloy with ca. 8.6 at% Sn. The surface composition was determined by low-energy ion-scattering (LEIS). The kinetics of the electrooxidation of CO and 2% CO/H₂ mixtures on Pt-Sn(IMP) is essentially identical to that of Pt₃Sn(110). The fact that any non-equilibrium composition can be easily prepared by this implantation method opens an interesting practical opportunity to create a new Pt-Sn alloy fuel cell catalyst having an otherwise unobtainable surface composition of Sn. This method also appears to have general utility in alloy catalysis as a means of exploring compositions in thermodynamically unfavorable regions of the bulk phase diagram. This revised version was published online in July 2006 with corrections to the Cover Date.     

Postembedding ultrastructural immunocytochemistry of neural antigens on tissues previously processed for routine light and electron microscopy: Preservation of antigenicity up to 22 years after initial fixation

A postembedding immunocytochemical technique is described that allows ultrastructural localization of glial fibrillary acidic protein and neuron-specific enolase on tissues originally processed only for routine light and electron microscopy. Use of the oxidizing agent sodium metaperiodate prior to incubation with the primary antiserum sufficiently removes osmium tetroxide (OsO₄) from potential antigen—antibody combining sites to allow specific localization of these neural antigens by colloidal gold immunolabelling. Both human and monkey neural tissues, prepared for routine ultrastructural examination with aldehyde fixatives and OsO₄ postfixation, show excellent ultrastructural morphology and antigen localization. In addition, formalin-fixed, paraffin-embedded pathological human brain tissues, obtained at autopsy up to 22 years previously, show good ultrastructural immunolocalization of glial fibrillary acidic protein when re-embedded for electron microscopy. Thus, ultrastructural immunolocalization of certain neural antigens is easily achieved in tissues originally processed for routine light and electron microscopy. This allows re-examination of archival tissues using current immunocy-tochemical advances, including that of selected pathological tissues previously prepared solely for light microscopy.     

Quality assurance of PASADENA hyperpolarization for 13C biomolecules

Object  Define MR quality assurance procedures for maximal PASADENA hyperpolarization of a biological ¹³C molecular imaging reagent. Materials and methods  An automated PASADENA polarizer and a parahydrogen generator were installed. ¹³C enriched hydroxyethyl acrylate, 1-¹³C, 2,3,3-d₃ (HEA), was converted to hyperpolarized hydroxyethyl propionate, 1-¹³C, 2,3,3-d₃ (HEP) and fumaric acid, 1-¹³C, 2,3-d₂ (FUM) to hyperpolarized succinic acid, 1-¹³C, 2,3-d₂ (SUC), by reaction with parahydrogen and norbornadiene rhodium catalyst. Incremental optimization of successive steps in PASADENA was implemented. MR spectra and in vivo images of hyperpolarized ¹³C imaging agents were acquired at 1.5 and 4.7 T. Results  Application of quality assurance (QA) criteria resulted in incremental optimization of the individual steps in PASADENA implementation. Optimal hyperpolarization of HEP of P = 20% was achieved by calibration of the NMR unit of the polarizer (B ₀ field strength ± 0.002 mT). Mean hyperpolarization of SUC, P = [15.3 ± 1.9]% (N = 16) in D ₂O, and P = [12.8 ± 3.1]% (N = 12) in H ₂O, was achieved every 5–8 min (range 13–20%). An in vivo ¹³C succinate image of a rat was produced. Conclusion  PASADENA spin hyperpolarization of SUC to 15.3% in average was demonstrated (37,400 fold signal enhancement at 4.7 T). The biological fate of ¹³C succinate, a normally occurring cellular intermediate, might be monitored with enhanced sensitivity.     

Development of an automated testing system for vehicle infotainment system

A current premium vehicle is implemented with a variety of information, entertainment, and communication functions, which are generally referred as an infotainment system. During vehicle development, testing of the infotainment system at an overall level is conventionally carried out manually by an expert who can observe at a customer level. This approach has significant limitations with regard to test coverage and effectiveness due to the complexity of the system functions and human’s capability. Hence, it is highly demanded by car manufacturers for an automated infotainment testing system, which replicates a human expert encompassing relevant sensory modalities relating to control (i.e., touch) and observation (i.e., sight and sound) of the system under test. This paper describes the design, development, and evaluation of such a system that consists of simulation of vehicle network, vision-based inspection, automated navigation of features, random cranking waveform generation, sound detection, and test automation. The system developed is able to: stimulate a vehicle system across a wide variety of initialisation conditions, exercise each function, check for system responses, and record failure situations for post-testing analysis.     

Situvis: A sensor data analysis and abstraction tool for pervasive computing systems

Pervasive systems are large-scale systems consisting of many sensors capturing numerous types of information. As this data is highly voluminous and dimensional, data analysis tasks can be extremely cumbersome and time-consuming. Enabling computers to recognise real-world situations is an even more difficult problem, involving not only data analysis, but also consistency checking. Here we present Situvis, an interactive visualisation tool for representing sensor data and creating higher-level abstractions from the data. This paper builds on previous work, Clear et al. (2009) [8] through evolved tool functionality and an evaluation of Situvis. A user-trial consisting of 10 participants shows that Situvis can be used to complete the key tasks in the development process of situation specifications in over 50% less time than an improvised alternative toolset.     

Quantitative pharmacophore models with inductive logic programming

Three-dimensional models, or pharmacophores, describing Euclidean constraints on the location on small molecules of functional groups (like hydrophobic groups, hydrogen acceptors and donors, etc.), are often used in drug design to describe the medicinal activity of potential drugs (or ‘ligands’). This medicinal activity is produced by interaction of the functional groups on the ligand with a binding site on a target protein. In identifying structure-activity relations of this kind there are three principal issues: (1) It is often difficult to “align” the ligands in order to identify common structural properties that may be responsible for activity; (2) Ligands in solution can adopt different shapes (or `conformations’) arising from torsional rotations about bonds. The 3-D molecular substructure is typically sought on one or more low-energy conformers; and (3) Pharmacophore models must, ideally, predict medicinal activity on some quantitative scale. It has been shown that the logical representation adopted by Inductive Logic Programming (ILP) naturally resolves many of the difficulties associated with the alignment and multi-conformation issues. However, the predictions of models constructed by ILP have hitherto only been nominal, predicting medicinal activity to be present or absent. In this paper, we investigate the construction of two kinds of quantitative pharmacophoric models with ILP: (a) Models that predict the probability that a ligand is “active”; and (b) Models that predict the actual medicinal activity of a ligand. Quantitative predictions are obtained by the utilising the following statistical procedures as background knowledge: logistic regression and naive Bayes, for probability prediction; linear and kernel regression, for activity prediction. The multi-conformation issue and, more generally, the relational representation used by ILP results in some special difficulties in the use of any statistical procedure. We present the principal issues and some solutions. Specifically, using data on the inhibition of the protease Thermolysin, we demonstrate that it is possible for an ILP program to construct good quantitative structure-activity models. We also comment on the relationship of this work to other recent developments in statistical relational learning. Editors: Tamás Horváth and Akihiro Yamamoto     

Pedestrian navigation aids: information requirements and design implications

Recent years have seen an increased interest in navigational services for pedestrians. To ensure that these services are successful, it is necessary to understand the information requirements of pedestrians when navigating, and in particular, what information they need and how it is used. A requirements study was undertaken to identify these information requirements within an urban navigation context. Results show that landmarks were by far the most predominant navigation cue, that distance information and street names were infrequently used, and that information is used to enable navigation decisions, but also to enhance the pedestrians confidence and trust. The implications for the design of pedestrian navigation aids are highlighted.