Probabilistic boundary element method

The purpose of the Probabilistic Structural Analysis Method (PSAM) project is to develop structural analysis capabilities for the design analysis of advanced space propulsion system hardware. The boundary element method (BEM) is used as the basis of the Probabilistic Advanced Analysis Methods (PADAM) which is discussed. The probabilistic BEM code (PBEM) is used to obtain the structural response and sensitivity results to a set of random variables. As such, PBEM performs analogous to other structural analysis codes such as finite elements in the PSAM system. For linear problems, unlike the finite element method (FEM), the BEM governing equations are written at the boundary of the body only, thus, the method eliminates the need to model the volume of the body. However, for general body force problems, a direct condensation of the governing equations to the boundary of the body is not possible and therefore volume modeling is generally required

Asymptotic Comparison of Method of Moments Estimators and Maximum Likelihood Estimators of Parameters in Zero-Inflated Poisson Model

This paper discusses the estimation of parameters in the zero-inflated Poisson (ZIP) model by the method of moments. The method of moments estimators (MMEs) are analytically compared with the maximum likelihood estimators (MLEs). The results of a modest simulation study are presented

In vitro and in vivo evaluation of cephalosporins for the treatment of Lyme disease.

BackgroundLyme disease accounts for >90% of all vector-borne disease cases in the United States and affect ~300,000 persons annually in North America. Though traditional tetracycline antibiotic therapy is generally prescribed for Lyme disease, still 10%-20% of patients treated with current antibiotic therapy still show lingering symptoms.MethodsIn order to identify new drugs, we have evaluated four cephalosporins as a therapeutic alternative to commonly used antibiotics for the treatment of Lyme disease by using microdilution techniques like minimum inhibitory concentration (MIC) and the minimum bactericidal concentration (MBC). We have determined the MIC and MBC of four drugs for three Borrelia burgdorferi s.s strains namely CA8, JLB31 and NP40. The binding studies were performed using in silico analysis.ResultsThe MIC order of the four drugs tested is cefoxitin (1.25 µM/mL) > cefamandole (2.5 µM/mL), > cefuroxime (5 µM/mL) > cefapirin (10 µM/mL). Among the drugs that are tested in this study using in vivo C3H/HeN mouse model, cefoxitin effectively kills B. burgdorferi. The in silico analysis revealed that all four cephalosporins studied binds effectively to B. burgdorferi proteins, SecA subunit penicillin-binding protein (PBP) and Outer surface protein E (OspE).ConclusionBased on the data obtained, cefoxitin has shown high efficacy killing B. burgdorferi at concentration of 1.25 µM/mL. In addition to it, cefoxitin cleared B. burgdorferi infection in C3H/HeN mice model at 20 mg/kg

Identification of New Drug Candidates Against \u3cem\u3eBorrelia burgdorferi\u3c/em\u3e Using High-Throughput Screening

Lyme disease is the most common zoonotic bacterial disease in North America. It is estimated that .300,000 cases per annum are reported in USA alone. A total of 10%–20% of patients who have been treated with antibiotic therapy report the recrudescence of symptoms, such as muscle and joint pain, psychosocial and cognitive difficulties, and generalized fatigue. This condition is referred to as posttreatment Lyme disease syndrome. While there is no evidence for the presence of viable infectious organisms in individuals with posttreatment Lyme disease syndrome, some researchers found surviving Borrelia burgdorferi population in rodents and primates even after antibiotic treatment. Although such observations need more ratification, there is unmet need for developing the therapeutic agents that focus on removing the persisting bacterial form of B. burgdorferi in rodent and nonhuman primates. For this purpose, high-throughput screening was done using BacTiter-Glo assay for four compound libraries to identify candidates that stop the growth of B. burgdorferi in vitro. The four chemical libraries containing 4,366 compounds (80% Food and Drug Administration [FDA] approved) that were screened are Library of Pharmacologically Active Compounds (LOPAC1280), the National Institutes of Health Clinical Collection, the Microsource Spectrum, and the Biomol FDA. We subsequently identified 150 unique compounds, which inhibited .90% of B. burgdorferi growth at a concentration of ,25 µM. These 150 unique compounds comprise many safe antibiotics, chemical compounds, and also small molecules from plant sources. Of the 150 unique compounds, 101 compounds are FDA approved. We selected the top 20 FDA-approved molecules based on safety and potency and studied their minimum inhibitory concentration and minimum bactericidal concentration. The promising safe FDA-approved candidates that show low minimum inhibitory concentration and minimum bactericidal concentration values can be chosen as lead molecules for further advanced studies

Investigation of failure mode interaction in laminated composites subjected to compression loading

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90657/1/AIAA-2011-1792-899.pd