Efficient Nonlinear Programming Algorithms for Chemical Process Control and Operations

Nonlinear programming (NLP) has been a key enabling tool for model-based decision-making in the chemical industry for over 50 years. Opti-mization is frequently applied in numerous ar-eas of chemical engineering including the de-velopment of process models from experimen-tal data, design of process flowsheets and equip-ment, planning and scheduling of chemical pro-cess operations, and the analysis of chemical pro-cesses under uncertainty and adverse conditions. These off-line tasks frequently require the solu-tion of NLPs formulated with detailed, lareg-scale process models. More recently, these tasks are complemented by time-critical, on-line optimization problem

First Observation of Coherent π0\pi^0 Production in Neutrino Nucleus Interactions with Eν<E_{\nu}< 2 GeV

The MiniBooNE experiment at Fermilab has amassed the largest sample to date of $\pi^0$s produced in neutral current (NC) neutrino-nucleus interactions at low energy. This paper reports a measurement of the momentum distribution of $\pi^0$s produced in mineral oil (CH$_2$) and the first observation of coherent $\pi^0$ production below 2 GeV. In the forward direction, the yield of events observed above the expectation for resonant production is attributed primarily to coherent production off carbon, but may also include a small contribution from diffractive production on hydrogen. Integrated over the MiniBooNE neutrino flux, the sum of the NC coherent and diffractive modes is found to be (19.5 $\pm$1.1 (stat) $\pm$2.5 (sys))% of all exclusive NC $\pi^0$ production at MiniBooNE. These measurements are of immediate utility because they quantify an important background to MiniBooNE's search for $\nu_{\mu} \to \nu_e$ oscillations.Comment: Submitted to Phys. Lett.

Towards Machine Wald

The past century has seen a steady increase in the need of estimating and predicting complex systems and making (possibly critical) decisions with limited information. Although computers have made possible the numerical evaluation of sophisticated statistical models, these models are still designed \emph{by humans} because there is currently no known recipe or algorithm for dividing the design of a statistical model into a sequence of arithmetic operations. Indeed enabling computers to \emph{think} as \emph{humans} have the ability to do when faced with uncertainty is challenging in several major ways: (1) Finding optimal statistical models remains to be formulated as a well posed problem when information on the system of interest is incomplete and comes in the form of a complex combination of sample data, partial knowledge of constitutive relations and a limited description of the distribution of input random variables. (2) The space of admissible scenarios along with the space of relevant information, assumptions, and/or beliefs, tend to be infinite dimensional, whereas calculus on a computer is necessarily discrete and finite. With this purpose, this paper explores the foundations of a rigorous framework for the scientific computation of optimal statistical estimators/models and reviews their connections with Decision Theory, Machine Learning, Bayesian Inference, Stochastic Optimization, Robust Optimization, Optimal Uncertainty Quantification and Information Based Complexity.Comment: 37 page

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Comparison of Breast Cancer Molecular Features and Survival by African and European Ancestry in The Cancer Genome Atlas

Importance: African Americans have the highest breast cancer mortality rate. Although racial difference in the distribution of intrinsic subtypes of breast cancer is known, it is unclear if there are other inherent genomic differences that contribute to the survival disparities. Objectives: To investigate racial differences in breast cancer molecular features and survival and to estimate the heritability of breast cancer subtypes. Design, Setting, and Participants: Among a convenience cohort of patients with invasive breast cancer, breast tumor and matched normal tissue sample data (as of September 18, 2015) were obtained from The Cancer Genome Atlas. Main Outcomes and Measures: Breast cancer–free interval, tumor molecular features, and genetic variants. Results: Participants were 930 patients with breast cancer, including 154 black patients of African ancestry (mean [SD] age at diagnosis, 55.66 [13.01] years; 98.1% [n = 151] female) and 776 white patients of European ancestry (mean [SD] age at diagnosis, 59.51 [13.11] years; 99.0% [n = 768] female). Compared with white patients, black patients had a worse breast cancer-free interval (hazard ratio, HR=1.67; 95% CI, 1.02-2.74; P = .043). They had a higher likelihood of basal-like (odds ratio, 3.80; 95% CI, 2.46-5.87; P < .001) and human epidermal growth factor receptor 2 (ERBB2 [formerly HER2])–enriched (odds ratio, 2.22; 95% CI, 1.10-4.47; P = .027) breast cancer subtypes, with the Luminal A subtype as the reference. Blacks had more TP53 mutations and fewer PIK3CA mutations than whites. While most molecular differences were eliminated after adjusting for intrinsic subtype, the study found 16 DNA methylation probes, 4 DNA copy number segments, 1 protein, and 142 genes that were differentially expressed, with the gene-based signature having an excellent capacity for distinguishing breast tumors from black vs white patients (cross-validation C index, 0.878). Using germline genotypes, the heritability of breast cancer subtypes (basal vs nonbasal) was estimated to be 0.436 (P = 1.5 × 10−14). The estrogen receptor–positive polygenic risk score built from 89 known susceptibility variants was higher in blacks than in whites (difference, 0.24; P = 2.3 × 10−5), while the estrogen receptor–negative polygenic risk score was much higher in blacks than in whites (difference, 0.48; P = 2.8 × 10−11). Conclusions and Relevance: On the molecular level, after adjusting for intrinsic subtype frequency differences, this study found a modest number of genomic differences but a significant clinical survival outcome difference between blacks and whites in The Cancer Genome Atlas data set. Moreover, more than 40% of breast cancer subtype frequency differences could be explained by genetic variants. These data could form the basis for the development of molecular targeted therapies to improve clinical outcomes for the specific subtypes of breast cancers that disproportionately affect black women. Findings also indicate that personalized risk assessment and optimal treatment could reduce deaths from aggressive breast cancers for black women

Test of Lorentz and CPT violation with Short Baseline Neutrino Oscillation Excesses

The sidereal time dependence of MiniBooNE electron neutrino and anti-electron neutrino appearance data are analyzed to search for evidence of Lorentz and CPT violation. An unbinned Kolmogorov-Smirnov test shows both the electron neutrino and anti-electron neutrino appearance data are compatible with the null sidereal variation hypothesis to more than 5%. Using an unbinned likelihood fit with a Lorentz-violating oscillation model derived from the Standard Model Extension (SME) to describe any excess events over background, we find that the electron neutrino appearance data prefer a sidereal time-independent solution, and the anti-electron neutrino appearance data slightly prefer a sidereal time-dependent solution. Limits of order 10E-20 GeV are placed on combinations of SME coefficients. These limits give the best limits on certain SME coefficients for muon neutrino to electron neutrino and anti-muon neutrino to anti-electron neutrino oscillations. The fit values and limits of combinations of SME coefficients are provided.Comment: 14 pages, 3 figures, and 2 tables, submitted to Physics Letters

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

Measurements of differential production cross sections for a Z boson in association with jets in pp collisions at root s=8 TeV

Peer reviewe

Search for the associated production of the Higgs boson with a top-quark pair

A search for the standard model Higgs boson produced in association with a top-quark pair t t ¯ H (tt¯H) is presented, using data samples corresponding to integrated luminosities of up to 5.1 fb &#8722;1 and 19.7 fb &#8722;1 collected in pp collisions at center-of-mass energies of 7 TeV and 8 TeV respectively. The search is based on the following signatures of the Higgs boson decay: H &#8594; hadrons, H &#8594; photons, and H &#8594; leptons. The results are characterized by an observed t t ¯ H tt¯H signal strength relative to the standard model cross section, &#956; = &#963;/&#963; SM ,under the assumption that the Higgs boson decays as expected in the standard model. The best fit value is &#956; = 2.8 ± 1.0 for a Higgs boson mass of 125.6 GeV

Measurement of prompt Jψ\psi pair production in pp collisions at \sqrt s = 7 Tev

Production of prompt J/ &#968; meson pairs in proton-proton collisions at s s&#8730; = 7 TeV is measured with the CMS experiment at the LHC in a data sample corresponding to an integrated luminosity of about 4.7 fb &#8722;1 . The two J/ &#968; mesons are fully reconstructed via their decays into &#956; + &#956; &#8722; pairs. This observation provides for the first time access to the high-transverse-momentum region of J/ &#968; pair production where model predictions are not yet established. The total and differential cross sections are measured in a phase space defined by the individual J/ &#968; transverse momentum ( p T J/ &#968; ) and rapidity (| y J/ &#968; |): | y J/ &#968; | 6.5 GeV/ c ; 1.2 4.5 GeV/ c . The total cross section, assuming unpolarized prompt J/ &#968; pair production is 1.49 ± 0.07 (stat) ±0.13 (syst) nb. Different assumptions about the J/ &#968; polarization imply modifications to the cross section ranging from &#8722;31% to +27%