The private Higgs

We introduce Higgs democracy in the Yukawa sector by constructing a model with a private Higgs and a dark scalar for each fermion thus addressing the large hierarchy among fermion masses. The model has interesting implications for the LHC, while the Standard Model phenomenology is recovered at low energies. We discuss some phenomenological implications such as FCNC, new Higgses at the TeV scale and dark matter candidates.     

Globally convergent homotopy algorithms for nonlinear systems of equations

Probability-one homotopy methods are a class of algorithms for solving nonlinear systems of equations that are accurate, robust, and converge from an arbitrary starting point almost surely. These new globally convergent homotopy techniques have been successfully applied to solve Brouwer fixed point problems, polynomial systems of equations, constrained and unconstrained optimization problems, discretizations of nonlinear two-point boundary value problems based on shooting, finite differences, collocation, and finite elements, and finite difference, collocation, and Galerkin approximations to nonlinear partial differential equations. This paper introduces, in a tutorial fashion, the theory of globally convergent homotopy algorithms, deseribes some computer algorithms and mathematical software, and presents several nontrivial engineering applications.This work was supported in part by DOE Grant DE-FG05-88ER25068, NASA Grant NAG-1-1079, and AFOSR Grant 89-0497.     

The Influence of Smoking Status on Exhaled Breath Profiles in Asthma and COPD Patients

Breath analysis using eNose technology can be used to discriminate between asthma and COPD patients, but it remains unclear whether results are influenced by smoking status. We aim to study whether eNose can discriminate between ever- vs. never-smokers and smoking <24 vs. >24 h before the exhaled breath, and if smoking can be considered a confounder that influences eNose results. We performed a cross-sectional analysis in adults with asthma or chronic obstructive pulmonary disease (COPD), and healthy controls. Ever-smokers were defined as patients with current or past smoking habits. eNose measurements were performed by using the SpiroNose. The principal component (PC) described the eNose signals, and linear discriminant analysis determined if PCs classified ever-smokers vs. never-smokers and smoking <24 vs. >24 h. The area under the receiver–operator characteristic curve (AUC) assessed the accuracy of the models. We selected 593 ever-smokers (167 smoked <24 h before measurement) and 303 never-smokers and measured the exhaled breath profiles of discriminated ever- and never-smokers (AUC: 0.74; 95% CI: 0.66–0.81), and no cigarette consumption <24h (AUC 0.54, 95% CI: 0.43–0.65). In healthy controls, the eNose did not discriminate between ever or never-smokers (AUC 0.54; 95% CI: 0.49–0.60) and recent cigarette consumption (AUC 0.60; 95% CI: 0.50–0.69). The eNose could distinguish between ever and never-smokers in asthma and COPD patients, but not recent smokers. Recent smoking is not a confounding factor of eNose breath profiles.     

Enumeration of RNA structures by matrix models

We enumerate the number of RNA contact structures according to their genus, i.e., the topological character of their pseudoknots. By using a recently proposed matrix model formulation for the RNA folding problem, we obtain exact results for the simple case of an RNA molecule with an infinitely flexible backbone, in which any arbitrary pair of bases is allowed. We analyze the distribution of the genus of pseudoknots as a function of the total number of nucleotides along the phosphate-sugar backbone.     

The neutrino mixing matrix could (almost) be diagonal with entries ±1

It is consistent with the measurement of _θ13∼0.15${\theta }_{13}\sim 0.15$ by Daya Bay to suppose that, in addition to being unitary, the neutrino mixing matrix is also almost Hermitian, and thereby only a small perturbation from diag(+1,−1,−1)$\mathrm{diag}(+1,-1,-1)$ in a suitable basis. We suggest this possibility simply as an easily falsifiable ansatz, as well as to offer a potentially useful means of organizing the experimental data. We explore the phenomenological implications of this ansatz and parametrize one type of deviation from the leading order relation |_Ve3|≈|_Vτ1|$|V_{e3}|\approx |V_{\tau 1}|$. We also emphasize the group-invariant angle between orthogonal matrices as a means of comparing to data. The discussion is purely phenomenological, without any attempt to derive the condition V^†≈V$V^{\mathrm{†}}\approx V$ from a fundamental theory.     

Efficient global optimization algorithm assisted by multiple surrogate techniques

Surrogate-based optimization proceeds in cycles. Each cycle consists of analyzing a number of designs, fitting a surrogate, performing optimization based on the surrogate, and finally analyzing a candidate solution. Algorithms that use the surrogate uncertainty estimator to guide the selection of the next sampling candidate are readily available, e.g., the efficient global optimization (EGO) algorithm. However, adding one single point at a time may not be efficient when the main concern is wall-clock time (rather than number of simulations) and simulations can run in parallel. Also, the need for uncertainty estimates limits EGO-like strategies to surrogates normally implemented with such estimates (e.g., kriging and polynomial response surface). We propose the multiple surrogate efficient global optimization (MSEGO) algorithm, which adds several points per optimization cycle with the help of multiple surrogates. We import uncertainty estimates from one surrogate to another to allow use of surrogates that do not provide them. The approach is tested on three analytic examples for nine basic surrogates including kriging, radial basis neural networks, linear Shepard, and six different instances of support vector regression. We found that MSEGO works well even with imported uncertainty estimates, delivering better results in a fraction of the optimization cycles needed by EGO.     

Photoacoustic spectrometer for accurate,continuous measurements of atmospheric carbon dioxide concentration

We have developed a portable photoacoustic spectrometer that offers routine, precise and accurate measurements of the molar concentration of atmospheric carbon. The temperature-controlled spectrometer continuously samples dried atmospheric air and employs an intensity-modulated distributed feedback laser and fiber amplifier operating near 1.57 µm. For measurements of carbon dioxide in air, we demonstrate a measurement precision (60-s averaging time) of 0.15 µmol mol^?1 and achieve a standard uncertainty of 0.8 µmol mol^?1 by calibrating the analyzer response in terms of certified gas mixtures. We also investigate how water vapor affects the photoacoustic signal by promoting collisional relaxation of the carbon dioxide.     

Profiling and semiquantitative analysis of the cell surface proteome in human mesenchymal stem cells

Mulitpotent mesenchymal stem cells (MSCs) derived from human bone marrow are promising candidates for the development of cell therapeutic strategies. MSC surface protein profiles provide novel biological knowledge concerning the proliferation and differentiation of these cells, including the potential for identifying therapeutic targets. Basic fibroblast growth factor (bFGF) affects cell surface proteins, which are associated with increased growth rate, differentiation potential, as well as morphological changes of MSCs in vitro. Cell surface proteins were isolated using a biotinylation-mediated method and identified using a combination of one-dimensional sodium dodecyl sulfate–polyacrylamide gel electrophoresis and mass spectrometry. The resulting gel lines were cut into 20 bands and digested with trypsin. Each tryptic fragment was analyzed by liquid chromatography–electrospray ionization tandem mass spectrometry. Proteins were identified using the Mascot search program and the International Protein Index human database. Noble MSC surface proteins (n?=?1,001) were identified from cells cultured either with (n?=?857) or without (n?=?667) bFGF-containing medium in three independent experiments. The proteins were classified using FatiGO to elucidate their function. We also confirmed the proteomics results using Western blotting and immunofluorescence microscopic analysis. The nature of the proteins identified makes it clear that MSCs express a wide variety of signaling molecules, including those related to cell differentiation. Among the latter proteins, four Ras-related Rab proteins, laminin-R, and three 14-3-3 proteins that were fractionated from MSCs cultured on bFGF-containing medium are implicated in bFGF-induced signal transduction of MSCs. Consequently, these finding provide insight into the understanding of the surface proteome of human MSCs.

Multidimensional separation of tryptic peptides from human serum proteins using reversed‐phase,strong cation exchange,weak anion exchange,and fused‐core fluorinated stationary phases

Proteome profiling of crude serum is a challenging task due to the wide dynamic range of protein concentrations and the presence of high‐abundance proteins, which cover >90% of the total protein mass in serum. Peptide fractionation on strong cation exchange, weak anion exchange in the electrostatic repulsion hydrophilic interaction chromatography (ERLIC) mode, RP C₁₈ at pH 2.5 (low pH), fused‐core fluorinated at pH 2.5, and RP C₁₈ at pH 9.7 (high pH) stationary phases resulted in two to three times more identified proteins and three to four times more identified peptides in comparison with 1D nanoChip‐LC–MS/MS quadrupole TOF analysis (45 proteins, 185 peptides). The largest number of peptides and proteins was identified after prefractionation in the ERLIC mode due to the more uniform distribution of peptides among the collected fractions and on the RP column at high pH due to the high efficiency of RP separations and the complementary selectivity of both techniques to low‐pH RP chromatography. A 3D separation scheme combining ERLIC, high‐pH RP, and low‐pH nanoChip‐LC–MS/MS for crude serum proteome profiling resulted in the identification of 208 proteins and 1088 peptides with the lowest reported concentration of 11 ng/mL for heat shock protein 74.