Logistic and Multiple Regression: The Two-Step Approach to Estimating Cost Growth

This study sought to predict cost growth in major Department of Defense (DoD) acquisition programs using logistic and multiple regression. In recent years, the use of statistical regression has proven to be successful in predicting the relationships associated with cost growth. This research follows on the work of Sipple (2002) and Bielecki (2003) and further explores the possibilities of using statistical regression to accurately estimate the dollar value associated with risk and uncertainty early in a program\u27s life cycle. In doing so, the author intends to reduce cost growth by increasing the accuracy of the original cost estimates subsequently used to compute cost growth. The author first used logistic regression to determine whether or not cost growth would occur in a program and, if so, continued with multiple regression to determine to what extent it would occur. Data were compiled from all DoD departments using the Selected Acquisition Reports published between 1990 and 2002. The study analyzes programs during the Engineering and Manufacturing Development phase in the Research and Development, Test and Evaluation (RDT&E) phase of acquisition. For the logistic regression portion of the research, the author produced a seven-variable model that accurately predicted 72 percent of the randomly selected validation data. For multiple regression, a six-variable model was produced that accurately predicted the amount of cost growth incurred for 91 percent of the programs that incurred cost growth. Results show that the two-step regression methodology offers a significant advantage over traditional methods by removing the data points that do not incur cost growth. The author concludes that there is no significant advantage gained by either isolating each cost variance category individually or combining them

Dual-comb spectroscopy with a phase-modulated probe comb for sub-MHz spectral sampling

We present a straightforward and efficient method to reduce the mode spacing of a frequency comb based on binary pseudo-random phase modulation of its pulse train. As a proof of concept, we use such a densified comb to perform dual-comb spectroscopy of a long-delay Mach–Zehnder interferometer and a high-quality-factor microresonator with sub-MHz spectral sampling. Since this approach is based on binary phase modulation, it combines all the advantages of other densification techniques: simplicity, single-step implementation, and conservation of the initial comb’s power

The protein that binds to DNA base J in trypanosomatids has features of a thymidine hydroxylase

© 2007 The Author et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/ by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The definitive version was published in Nucleic Acids Research 35 (2007): 2107-2115, doi:10.1093/nar/gkm049.Trypanosomatids contain an unusual DNA base J (ß-D-glucosylhydroxymethyluracil), which replaces a fraction of thymine in telomeric and other DNA repeats. To determine the function of base J, we have searched for enzymes that catalyze J biosynthesis. We present evidence that a protein that binds to J in DNA, the J-binding protein 1 (JBP1), may also catalyze the first step in J biosynthesis, the conversion of thymine in DNA into hydroxymethyluracil. We show that JBP1 belongs to the family of Fe2+ and 2-oxoglutarate-dependent dioxygenases and that replacement of conserved residues putatively involved in Fe2+ and 2-oxoglutarate-binding inactivates the ability of JBP1 to contribute to J synthesis without affecting its ability to bind to J-DNA. We propose that JBP1 is a thymidine hydroxylase responsible for the local amplification of J inserted by JBP2, another putative thymidine hydroxylase.This work was funded by a grant from the Netherlands Organization for Scientific Research and Chemical Sciences (NWO-CW) to P.B., NIH grant A1063523 to R.S. and NIH grant GM063584 to R.P.H

Exome Sequencing in Suspected Monogenic Dyslipidemias

Abstract BACKGROUND: -Exome sequencing is a promising tool for gene mapping in Mendelian disorders. We utilized this technique in an attempt to identify novel genes underlying monogenic dyslipidemias. METHODS AND RESULTS: -We performed exome sequencing on 213 selected family members from 41 kindreds with suspected Mendelian inheritance of extreme levels of low-density lipoprotein (LDL) cholesterol (after candidate gene sequencing excluded known genetic causes for high LDL cholesterol families) or high-density lipoprotein (HDL) cholesterol. We used standard analytic approaches to identify candidate variants and also assigned a polygenic score to each individual in order to account for their burden of common genetic variants known to influence lipid levels. In nine families, we identified likely pathogenic variants in known lipid genes (ABCA1, APOB, APOE, LDLR, LIPA, and PCSK9); however, we were unable to identify obvious genetic etiologies in the remaining 32 families despite follow-up analyses. We identified three factors that limited novel gene discovery: (1) imperfect sequencing coverage across the exome hid potentially causal variants; (2) large numbers of shared rare alleles within families obfuscated causal variant identification; and (3) individuals from 15% of families carried a significant burden of common lipid-related alleles, suggesting complex inheritance can masquerade as monogenic disease. CONCLUSIONS: -We identified the genetic basis of disease in nine of 41 families; however, none of these represented novel gene discoveries. Our results highlight the promise and limitations of exome sequencing as a discovery technique in suspected monogenic dyslipidemias. Considering the confounders identified may inform the design of future exome sequencing studies

A cognitive prosthesis for complex decision-making

While simple heuristics can be ecologically rational and effective in naturalistic decision making contexts, complex situations require analytical decision making strategies, hypothesis-testing and learning. Sub-optimal decision strategies – using simplified as opposed to analytic decision rules – have been reported in domains such as healthcare, military operational planning, and government policy making. We investigate the potential of a computational toolkit called “IMAGE” to improve decision-making by developing structural knowledge and increasing understanding of complex situations. IMAGE is tested within the context of a complex military convoy management task through (a) interactive simulations, and (b) visualization and knowledge representation capabilities. We assess the usefulness of two versions of IMAGE (desktop and immersive) compared to a baseline. Results suggest that the prosthesis helped analysts in making better decisions, but failed to increase their structural knowledge about the situation once the cognitive prosthesis is removed

The complete genome sequence of Moorella thermoacetica (f. Clostridium thermoaceticum )

This paper describes the genome sequence of Moorella thermoacetica (f. Clostridium thermoaceticum ), which is the model acetogenic bacterium that has been widely used for elucidating the Wood–Ljungdahl pathway of CO and CO 2 fixation. This pathway, which is also known as the reductive acetyl-CoA pathway, allows acetogenic (often called homoacetogenic) bacteria to convert glucose stoichiometrically into 3 mol of acetate and to grow autotrophically using H 2 and CO as electron donors and CO 2 as an electron acceptor. Methanogenic archaea use this pathway in reverse to grow by converting acetate into methane and CO 2 . Acetogenic bacteria also couple the Wood–Ljungdahl pathway to a variety of other pathways to allow the metabolism of a wide variety of carbon sources and electron donors (sugars, carboxylic acids, alcohols and aromatic compounds) and electron acceptors (CO 2 , nitrate, nitrite, thiosulfate, dimethylsulfoxide and aromatic carboxyl groups). The genome consists of a single circular 2 628 784 bp chromosome encoding 2615 open reading frames (ORFs), which includes 2523 predicted protein-encoding genes. Of these, 1834 genes (70.13%) have been assigned tentative functions, 665 (25.43%) matched genes of unknown function, and the remaining 24 (0.92%) had no database match. A total of 2384 (91.17%) of the ORFs in the M. thermoacetica genome can be grouped in orthologue clusters. This first genome sequence of an acetogenic bacterium provides important information related to how acetogens engage their extreme metabolic diversity by switching among different carbon substrates and electron donors/acceptors and how they conserve energy by anaerobic respiration. Our genome analysis indicates that the key genetic trait for homoacetogenesis is the core acs gene cluster of the Wood–Ljungdahl pathway.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75588/1/j.1462-2920.2008.01679.x.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/75588/2/EMI_1679_sm_Table_S1-S7_and_Figure_S1-S7.pd

Report from Working Group 3: Beyond the standard model physics at the HL-LHC and HE-LHC

This is the third out of five chapters of the final report [1] of the Workshop on Physics at HL-LHC, and perspectives on HE-LHC [2]. It is devoted to the study of the potential, in the search for Beyond the Standard Model (BSM) physics, of the High Luminosity (HL) phase of the LHC, defined as $3$ ab$^{-1}$ of data taken at a centre-of-mass energy of 14 TeV, and of a possible future upgrade, the High Energy (HE) LHC, defined as $15$ ab$^{-1}$ of data at a centre-of-mass energy of 27 TeV. We consider a large variety of new physics models, both in a simplified model fashion and in a more model-dependent one. A long list of contributions from the theory and experimental (ATLAS, CMS, LHCb) communities have been collected and merged together to give a complete, wide, and consistent view of future prospects for BSM physics at the considered colliders. On top of the usual standard candles, such as supersymmetric simplified models and resonances, considered for the evaluation of future collider potentials, this report contains results on dark matter and dark sectors, long lived particles, leptoquarks, sterile neutrinos, axion-like particles, heavy scalars, vector-like quarks, and more. Particular attention is placed, especially in the study of the HL-LHC prospects, to the detector upgrades, the assessment of the future systematic uncertainties, and new experimental techniques. The general conclusion is that the HL-LHC, on top of allowing to extend the present LHC mass and coupling reach by $20-50\%$ on most new physics scenarios, will also be able to constrain, and potentially discover, new physics that is presently unconstrained. Moreover, compared to the HL-LHC, the reach in most observables will, generally more than double at the HE-LHC, which may represent a good candidate future facility for a final test of TeV-scale new physics