Applying Tabu Heuristic to Wind Influenced, Minimum Risk and Maximum Expected Coverage Routes

The purpose of this thesis is to provide Air Combat Command a method for determining the number of predator unmanned aerial vehicles (UAVs) required to cover a pre-selected target. Extending previous research that employs reactive TABU search methods for deterministic vehicle routing problems, this thesis incorporates wind effects that can significantly alter the travel times for any given scenario. Additionally, it accounts for possible attrition by introducing minimum risk route and expected number of target covered to the objective function. The results of the TABU search and subsequent Monte-Carlo simulation: gives the number of predator\u27s required to cover a target set, identifies \u27robust\u27 routes, and suggests routes that increase expected number of targets covered while reducing losses

A Model-Based Bayesian Estimation of the Rate of Evolution of VNTR Loci in Mycobacterium tuberculosis

Variable numbers of tandem repeats (VNTR) typing is widely used for studying the bacterial cause of tuberculosis. Knowledge of the rate of mutation of VNTR loci facilitates the study of the evolution and epidemiology of Mycobacterium tuberculosis. Previous studies have applied population genetic models to estimate the mutation rate, leading to estimates varying widely from around to per locus per year. Resolving this issue using more detailed models and statistical methods would lead to improved inference in the molecular epidemiology of tuberculosis. Here, we use a model-based approach that incorporates two alternative forms of a stepwise mutation process for VNTR evolution within an epidemiological model of disease transmission. Using this model in a Bayesian framework we estimate the mutation rate of VNTR in M. tuberculosis from four published data sets of VNTR profiles from Albania, Iran, Morocco and Venezuela. In the first variant, the mutation rate increases linearly with respect to repeat numbers (linear model); in the second, the mutation rate is constant across repeat numbers (constant model). We find that under the constant model, the mean mutation rate per locus is (95% CI: ,)and under the linear model, the mean mutation rate per locus per repeat unit is (95% CI: ,). These new estimates represent a high rate of mutation at VNTR loci compared to previous estimates. To compare the two models we use posterior predictive checks to ascertain which of the two models is better able to reproduce the observed data. From this procedure we find that the linear model performs better than the constant model. The general framework we use allows the possibility of extending the analysis to more complex models in the future

Reconstruction of the Talkeetna intraoceanic arc of Alaska through thermobarometry

Author Posting. © American Geophysical Union, 2008. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 113 (2008): B03204, doi:10.1029/2007JB005208.The Talkeetna arc is one of two intraoceanic arcs where much of the section from the upper mantle through the volcanic carapace is well exposed. We reconstruct the vertical section of the Talkeetna arc by determining the (re)crystallization pressures at various structural levels. The thermobarometry shows that the tonalites and quartz diorites intruded at ∼5–9 km into a volcanic section estimated from stratigraphy to be 7 km thick. The shallowest, Tazlina and Barnette, gabbros crystallized at ∼17–24 km; the Klanelneechena Klippe crystallized at ∼24–26 km; and the base of the arc crystallized at ∼35 km depth. The arc had a volcanic:plutonic ratio of ∼1:3–1:4. However, many or most of the felsic plutonic rocks may represent crystallized liquids rather than cumulates so that the liquid:cumulate ratio might be 1:2 or larger. The current 5- to 7-km structural thickness of the plutonic section of the arc is ∼15–30% of the original 23- to 28-km thickness. The bulk composition of the original Talkeetna arc section was ∼51–58 wt % SiO2.Funded by NSF EAR-9910899

Nanostructures, Technology, Research, and Applications

Contains reports on twenty research projects and a list of publications.Joint Services Electronics Program Grant DAAH04-95-1-0038National Science Foundation Grant ECS-94-07078Semiconductor Research CorporationU.S. Army Research Office Grant DAAH04-95-1-0564Defense Advanced Research Projects Agency/Naval Air Systems Command Contract N00019-95-K-0131National Aeronautics and Space Administration Contract NAS8-38249National Aeronautics and Space Administration Grant NAGW-2003IBM Corporation Contract 1622National Science Foundation Graduate FellowshipU.S. Navy - Office of Naval Research Grant N00014-95-1-1297U.S. Army Research Office Contract DAAH04-94-G-0377U.S. Air Force - Office of Scientific Research Grant F49620-92-J-0064U.S. Air Force - Office of Scientific Research Grant F49620-95-1-0311National Science Foundation Contract DMR 94-0034U.S. Air Force - Office of Scientific Research Contract F49620-96-0126Harvard-Smithsonian Astrophysical Observatory Contract SV630304National Aeronautics and Space Administration Grant NAG5-5105Los Alamos National Laboratory Contract E57800017-9

Nanostructures Technology, Research, and Applications

Contains reports on twenty-four research projects and a list of publications.Joint Services Electronics Program Grant DAAHO4-95-1-0038Defense Advanced Research Projects Agency/Semiconductor Research Corporation SA1645-25508PGU.S. Army Research Office Grant DAAHO4-95-1-0564Defense Advanced Research Projects Agency/U.S. Navy - Naval Air Systems Command Contract N00019-95-K-0131Suss Advanced Lithography P. O. 51668National Aeronautics and Space Administration Contract NAS8-38249National Aeronautics and Space Administration Grant NAGW-2003Defense Advanced Research Projects Agency/U.S. Army Research Office Grant DAAHO4-951-05643M CorporationDefense Advanced Research Projects Agency/U.S. Navy - Office of Naval Research Contract N66001-97-1-8909National Science Foundation Graduate FellowshipU.S. Army Research Office Contract DAAHO4-94-G-0377National Science Foundation Contract DMR-940034National Science Foundation Grant DMR 94-00334Defense Advanced Research Projects Agency/U.S. Air Force - Office of Scientific Research Contract F49620-96-1-0126Harvard-Smithsonian Astrophysical Observatory Contract SV630304National Aeronautics and Space Administration Grant NAG5-5105Los Alamos National Laboratory Contract E57800017-9GSouthwest Research Institute Contract 83832MIT Lincoln Laboratory Advanced Concepts ProgramMIT Lincoln Laboratory Contract BX-655

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Using Approximate Bayesian Computation to Estimate Tuberculosis Transmission Parameters From Genotype Data

Tuberculosis can be studied at the population level by genotyping strains of Mycobacterium tuberculosis isolated from patients. We use an approximate Bayesian computational method in combination with a stochastic model of tuberculosis transmission and mutation of a molecular marker to estimate the net transmission rate, the doubling time, and the reproductive value of the pathogen. This method is applied to a published data set from San Francisco of tuberculosis genotypes based on the marker IS6110. The mutation rate of this marker has previously been studied, and we use those estimates to form a prior distribution of mutation rates in the inference procedure. The posterior point estimates of the key parameters of interest for these data are as follows: net transmission rate, 0.69/year [95% credibility interval (C.I.) 0.38, 1.08]; doubling time, 1.08 years (95% C.I. 0.64, 1.82); and reproductive value 3.4 (95% C.I. 1.4, 79.7). These figures suggest a rapidly spreading epidemic, consistent with observations of the resurgence of tuberculosis in the United States in the 1980s and 1990s

Inferences on the acquisition of multi-drug resistance in Mycobacterium tuberculosis using molecular epidemiological data

Tuberculosis (TB) is a lung disease caused by the bacterium Mycobacterium tuberculosis, which kills around 1.5 million people each year and remains a serious challenge for global public health. This chapter investigates the rates of drug resistance acquisition in a natural population using molecular epidemiological data from Bolivia. It explains the rate of direct acquisition of double resistance from the double sensitive state within patients and compares it to the rates of evolution to single resistance. The chapter addresses whether or not double resistance can evolve directly from a double sensitive state within a given host. It disregards latent infections for simplicity and focuses on active infections which are the larger source of new infections. The chapter estimates epidemiological parameters describing the acquisition of multi-drug resistance in M. tuberculosis from molecular epidemiological data using approximate Bayesian computation. It concludes that the evidence favours the drugs being acquired at different rates, specifically, isoniazid resistance evolves faster than rifampicin resistance