Exploration of new multivariate spectral calibration algorithms.

A variety of multivariate calibration algorithms for quantitative spectral analyses were investigated and compared, and new algorithms were developed in the course of this Laboratory Directed Research and Development project. We were able to demonstrate the ability of the hybrid classical least squares/partial least squares (CLSIPLS) calibration algorithms to maintain calibrations in the presence of spectrometer drift and to transfer calibrations between spectrometers from the same or different manufacturers. These methods were found to be as good or better in prediction ability as the commonly used partial least squares (PLS) method. We also present the theory for an entirely new class of algorithms labeled augmented classical least squares (ACLS) methods. New factor selection methods are developed and described for the ACLS algorithms. These factor selection methods are demonstrated using near-infrared spectra collected from a system of dilute aqueous solutions. The ACLS algorithm is also shown to provide improved ease of use and better prediction ability than PLS when transferring calibrations between near-infrared calibrations from the same manufacturer. Finally, simulations incorporating either ideal or realistic errors in the spectra were used to compare the prediction abilities of the new ACLS algorithm with that of PLS. We found that in the presence of realistic errors with non-uniform spectral error variance across spectral channels or with spectral errors correlated between frequency channels, ACLS methods generally out-performed the more commonly used PLS method. These results demonstrate the need for realistic error structure in simulations when the prediction abilities of various algorithms are compared. The combination of equal or superior prediction ability and the ease of use of the ACLS algorithms make the new ACLS methods the preferred algorithms to use for multivariate spectral calibrations

Valsartan (Profiles of Drugs Substances, Excipients and Related Methodology)

Valsartan is an antihypertensive drug which selectively inhibits angiotensin receptor type II. This tetrazole derivative was first developed by Novartis and marketed under brand name Diovan® . This compound is orally active and is rapidly absorbed after oral doses, having a bioavailability of approximately 23% . Valsartan appears as a white or almost white hygroscopic powder. This compound must be kept in an air-tight container and should be protected from light and heat. It is available in film-coated tablets containing valsartan 40, 80, 160, or 320 mg, and capsules with dosage of 80 or 160 mg. Tablet combinations of valsartan with hydrochlorothiazide or amlodipine are also availabl

SOSORT consensus paper: school screening for scoliosis. Where are we today?

This report is the SOSORT Consensus Paper on School Screening for Scoliosis discussed at the 4th International Conference on Conservative Management of Spinal Deformities, presented by SOSORT, on May 2007. The objectives were numerous, 1) the inclusion of the existing information on the issue, 2) the analysis and discussion of the responses by the meeting attendees to the twenty six questions of the questionnaire, 3) the impact of screening on frequency of surgical treatment and of its discontinuation, 4) the reasons why these programs must be continued, 5) the evolving aim of School Screening for Scoliosis and 6) recommendations for improvement of the procedure

Personal Papers (MS 80-0002)

Dividend from Merck & Co., Inc. to Our Stockholders enclosing the regular quarterly dividend of $1.00 per share on the Convertible Second Preferred Stock of the Merck & Co., Inc