Agilent Technologies

About: Agilent Technologies is a company organization based out in Santa Clara, California, United States. It is known for research contribution in the topics: Signal & Mass spectrometry. The organization has 7398 authors who have published 11518 publications receiving 262410 citations. The organization is also known as: Agilent Technologies, Inc..

System and method for reducing power consumption in an optical screen pointing device

Abstract: An apparatus for controlling the position of a screen pointer for an electronic device having a display screen includes a light source for illuminating an imaging surface, thereby generating reflected images. The apparatus includes a motion transducer. A lens receives the reflected images and directs the reflected images onto the motion transducer. The motion transducer includes an electronic shutter for controlling the amount of time that light is collected for image frames. The motion transducer is configured to generate digital representations of the reflected images. The motion transducer is configured to generate movement data based on the digital representations of the reflected images. The movement data is indicative of relative motion between the imaging surface and the motion transducer. A controller coupled to the light source turns the light source on only during the time that light is being collected for an image frame.

Protein network prediction and topological analysis in Leishmania major as a tool for drug target selection

Abstract: Background: Leishmaniasis is a virulent parasitic infection that causes a worldwide disease burden. Most treatments have toxic side-effects and efficacy has decreased due to the emergence of resistant strains. The outlook is worsened by the absence of promising drug targets for this disease. We have taken a computational approach to the detection of new drug targets, which may become an effective strategy for the discovery of new drugs for this tropical disease. Results: We have predicted the protein interaction network of Leishmania major by using three validated methods: PSIMAP, PEIMAP, and iPfam. Combining the results from these methods, we calculated a high confidence network (confidence score > 0.70) with 1,366 nodes and 33,861 interactions. We were able to predict the biological process for 263 interacting proteins by doing enrichment analysis of the clusters detected. Analyzing the topology of the network with metrics such as connectivity and betweenness centrality, we detected 142 potential drug targets after homology filtering with the human proteome. Further experiments can be done to validate these targets. Conclusion: We have constructed the first protein interaction network of the Leishmania major parasite by using a computational approach. The topological analysis of the protein network enabled us to identify a set of candidate proteins that may be both (1) essential for parasite survival and (2) without human orthologs. These potential targets are promising for further experimental validation. This strategy, if validated, may augment established drug discovery methodologies, for this and possibly other tropical diseases, with a relatively low additional investment of time and resources.

Absolute structure determination of compounds with axial and planar chirality using the crystalline sponge method

Abstract: The absolute stereochemistry of compounds with axial and planar chirality is successfully determined by the crystalline sponge method without crystallization or derivatization of the compounds. This method is applied to absolute structure determination in the asymmetric synthesis of unique compounds with axial and planar chirality.

Methods and apparatus for detecting temporal process variation and for managing and predicting performance of automatic classifiers

Abstract: Techniques for detecting temporal process variation and for managing and predicting performance of automatic classifiers applied to such processes using performance estimates based on temporal ordering of the samples are presented

Analytical Expressions for the Power Spectral Density of CP-OFDM and ZP-OFDM Signals

Abstract: In this letter, analytical expressions are derived for the power spectral density (PSD) of orthogonal frequency division multiplex (OFDM) signals employing a cyclic prefix (CP-OFDM) or zero padding (ZP-OFDM) time guard interval. Under the relatively weak assumptions that (i) the data are independent and identically distributed on all OFDM subcarriers and (ii) the OFDM pulse shape is sufficiently localized in time, simple closed-form PSD expressions can be obtained. These expressions are then compared to existing OFDM PSD expressions and validated by inspecting the power spectra of some standardized OFDM signals.