Autonomous Mobile Vehicle based on RFID Technology using an ARM7 Microcontroller

Radio Frequency Identification (RFID) system is looked upon as one of the top ten important technologies in the 20th century. Industrial automation application is one of the key issues in developing RFID. Therefore, this paper designs and implements a RFID-based autonomous mobile vehicle for more extensively application of RFID systems. The microcontroller LPC2148 is used to control the autonomous mobile vehicle and to communicate with RFID reader. By storing the moving control commands such as turn right, turn left, speed up and speed down etc. into the RFID tags beforehand and sticking the tags on the tracks, the autonomous mobile vehicle can then read the moving control commands from the tags and accomplish the proper actions. Due to the convenience and non-contact characteristic of RFID systems, the proposed mobile vehicle has great potential to be used for industrial automation, goods transportation, data transmission, and unmanned medical nursing etc. in the future. Experimental results demonstrate the validity of the proposed mobile vehicle

High spatial resolution restoration of IRAS images

A general technique to improve the spatial resolution of the IRAS AO data was developed at The Aerospace Corporation using the Maximum Entropy algorithm of Skilling and Gull. The technique has been applied to a variety of fields and several individual AO MACROS. With this general technique, resolutions of 15 arcsec were achieved in 12 and 25 micron images and 30 arcsec in 60 and 100 micron images. Results on galactic plane fields show that both photometric and positional accuracy achieved in the general IRAS survey are also achieved in the reconstructed images

A statistical inference approach for the retrieval of the atmospheric ozone profile from simulated satellite measurements of solar backscattered ultraviolet radiation

NASA's Mission to Planet Earth (MTPE) will address important interdisciplinary and environmental issues such as global warming, ozone depletion, deforestation, acid rain, and the like with its long term satellite observations of the Earth and with its comprehensive Data and Information System. Extensive sets of satellite observations supporting MTPE will be provided by the Earth Observing System (EOS), while more specific process related observations will be provided by smaller Earth Probes. MTPE will use data from ground and airborne scientific investigations to supplement and validate the global observations obtained from satellite imagery, while the EOS satellites will support interdisciplinary research and model development. This is important for understanding the processes that control the global environment and for improving the prediction of events. In this paper we illustrate the potential for powerful artificial intelligence (AI) techniques when used in the analysis of the formidable problems that exist in the NASA Earth Science programs and of those to be encountered in the future MTPE and EOS programs. These techniques, based on the logical and probabilistic reasoning aspects of plausible inference, strongly emphasize the synergetic relation between data and information. As such, they are ideally suited for the analysis of the massive data streams to be provided by both MTPE and EOS. To demonstrate this, we address both the satellite imagery and model enhancement issues for the problem of ozone profile retrieval through a method based on plausible scientific inferencing. Since in the retrieval problem, the atmospheric ozone profile that is consistent with a given set of measured radiances may not be unique, an optimum statistical method is used to estimate a 'best' profile solution from the radiances and from additional a priori information

Genetic disruption of N-RasG12D palmitoylation perturbs hematopoiesis and prevents myeloid transformation in mice.

Oncogenic RAS mutations pose substantial challenges for rational drug discovery. Sequence variations within the hypervariable region of Ras isoforms underlie differential posttranslational modification and subcellular trafficking, potentially resulting in selective vulnerabilities. Specifically, inhibiting the palmitoylation/depalmitoylation cycle is an appealing strategy for treating NRAS mutant cancers, particularly as normal tissues would retain K-Ras4b function for physiologic signaling. The role of endogenous N-RasG12D palmitoylation in signal transduction, hematopoietic differentiation, and myeloid transformation is unknown, and addressing these key questions will inform efforts to develop mechanism-based therapies. To evaluate the palmitoylation/depalmitoylation cycle as a candidate drug target in an in vivo disease-relevant model system, we introduced a C181S mutation into a conditional NrasG12D "knock-in" allele. The C181S second-site amino acid substitution abrogated myeloid transformation by NrasG12D, which was associated with mislocalization of the nonpalmitoylated N-Ras mutant protein, reduced Raf/MEK/ERK signaling, and alterations in hematopoietic stem and progenitor populations. Furthermore, hematologic malignancies arising in NrasG12D/G12D,C181S compound heterozygous mice invariably acquired revertant mutations that restored cysteine 181. Together, these studies validate the palmitoylation cycle as a promising therapeutic target in NRAS mutant cancers

ABHD17 regulation of plasma membrane palmitoylation and N-Ras-dependent cancer growth

Multiple Ras proteins, including N-Ras, depend on a palmitoylation/depalmitoylation cycle to regulate their subcellular trafficking and oncogenicity. General lipase inhibitors such as Palmostatin M (Palm M) block N-Ras depalmitoylation, but lack specificity and target several enzymes displaying depalmitoylase activity. Here, we describe ABD957, a potent and selective covalent inhibitor of the ABHD17 family of depalmitoylases, and show that this compound impairs N-Ras depalmitoylation in human acute myeloid leukemia (AML) cells. ABD957 produced partial effects on N-Ras palmitoylation compared with Palm M, but was much more selective across the proteome, reflecting a plasma membrane-delineated action on dynamically palmitoylated proteins. Finally, ABD957 impaired N-Ras signaling and the growth of NRAS-mutant AML cells in a manner that synergizes with MAP kinase kinase (MEK) inhibition. Our findings uncover a surprisingly restricted role for ABHD17 enzymes as regulators of the N-Ras palmitoylation cycle and suggest that ABHD17 inhibitors may have value as targeted therapies for NRAS-mutant cancers