Experimental Resonance Enhanced Multiphoton Ionization (REMPI) studies of small molecules

Resonance enhanced multiphoton ionization (REMPI) utilizes tunable dye lasers to ionize an atom or molecule by first preparing an excited state by multiphoton absorption and then ionizing that state before it can decay. This process is highly selective with respect to both the initial and resonant intermediate states of the target, and it can be extremely sensitive. In addition, the products of the REMPI process can be detected as needed by analyzing the resulting electrons, ions, fluorescence, or by additional REMPI. This points to a number of exciting opportunities for both basic and applied science. On the applied side, REMPI has great potential as an ultrasensitive, highly selective detector for trace, reactive, or transient species. On the basic side, REMPI affords an unprecedented means of exploring excited state physics and chemistry at the quantum-state-specific level. An overview of current studies of excited molecular states is given to illustrate the principles and prospects of REMPI

Information inequalities and Generalized Graph Entropies

In this article, we discuss the problem of establishing relations between information measures assessed for network structures. Two types of entropy based measures namely, the Shannon entropy and its generalization, the R\'{e}nyi entropy have been considered for this study. Our main results involve establishing formal relationship, in the form of implicit inequalities, between these two kinds of measures when defined for graphs. Further, we also state and prove inequalities connecting the classical partition-based graph entropies and the functional-based entropy measures. In addition, several explicit inequalities are derived for special classes of graphs.Comment: A preliminary version. To be submitted to a journa

Rotationally resolved energy-dispersive photoelectron spectroscopy of H_2O: Photoionization of the C̃(0,0,0) state at 355 nm

Measured and calculated rotationally resolved photoelectron spectra for photoionization of low rotational levels of the C̃^1B_1 Rydberg state of water are reported. This is the first example of rotationally resolved photoionization spectra beyond the special cases of H_2, high-J levels, and threshold spectra. These spectra reveal very nonatomiclike behavior and, surprisingly, the influence of multiple Cooper minima in the photoelectron matrix elements

Information Indices with High Discriminative Power for Graphs

In this paper, we evaluate the uniqueness of several information-theoretic measures for graphs based on so-called information functionals and compare the results with other information indices and non-information-theoretic measures such as the well-known Balaban index. We show that, by employing an information functional based on degree-degree associations, the resulting information index outperforms the Balaban index tremendously. These results have been obtained by using nearly 12 million exhaustively generated, non-isomorphic and unweighted graphs. Also, we obtain deeper insights on these and other topological descriptors when exploring their uniqueness by using exhaustively generated sets of alkane trees representing connected and acyclic graphs in which the degree of a vertex is at most four

Spectral analysis of Gene co-expression network of Zebrafish

We analyze the gene expression data of Zebrafish under the combined framework of complex networks and random matrix theory. The nearest neighbor spacing distribution of the corresponding matrix spectra follows random matrix predictions of Gaussian orthogonal statistics. Based on the eigenvector analysis we can divide the spectra into two parts, first part for which the eigenvector localization properties match with the random matrix theory predictions, and the second part for which they show deviation from the theory and hence are useful to understand the system dependent properties. Spectra with the localized eigenvectors can be characterized into three groups based on the eigenvalues. We explore the position of localized nodes from these different categories. Using an overlap measure, we find that the top contributing nodes in the different groups carry distinguished structural features. Furthermore, the top contributing nodes of the different localized eigenvectors corresponding to the lower eigenvalue regime form different densely connected structure well separated from each other. Preliminary biological interpretation of the genes, associated with the top contributing nodes in the localized eigenvectors, suggests that the genes corresponding to same vector share common features.Comment: 6 pages, four figures (accepted in EPL

Scientific Potential and Design Considerations for an Undulator Beam Line on Aladdin Storage Ring

The unique features of undulator radiation, i.e., high photon flux and brightness, partial coherence, small beam divergence, spectral tunability, etc., mandate that undulators be included in the future plans for Aladdin. This will make it possible to perform the next generation of experiments in photon-stimulated spectroscopies. A team of scientists (see Appendix) has now been assembled to build an insertion device (ID) and the associated beam line at Aladdin. In considering the specifications for the ID, it was assumed that the ID beamline will be an SRC user facility. Consequently, design parameters were chosen with the intent of maximizing experimental flexibility consistent with a conservative design approach. A tunable {open_quotes}clamshell{close_quotes} undulator device was Chosen with a first harmonic tunable from 35 to 110 eV to operate on a 1 GeV storage ring. Higher harmonics will be utilized for experiments needing higher photon energies

Connections between Classical and Parametric Network Entropies

This paper explores relationships between classical and parametric measures of graph (or network) complexity. Classical measures are based on vertex decompositions induced by equivalence relations. Parametric measures, on the other hand, are constructed by using information functions to assign probabilities to the vertices. The inequalities established in this paper relating classical and parametric measures lay a foundation for systematic classification of entropy-based measures of graph complexity

Modeled Health and Economic Impact of Team-Based Care for Hypertension

IntroductionTeam-based interventions for hypertension care have been widely studied and shown effective in improving hypertension outcomes. Few studies have evaluated long-term effects of these interventions; none have assessed broad-scale implementation. This study estimates the prospective health, economic, and budgetary impact of universal adoption of a team-based care intervention model that targets people with treated but uncontrolled hypertension in the U.S.MethodsAnalysis was conducted in 2014−2015 using a microsimulation model, constructed with various data sources from 1948 to 2014, designed to evaluate prospective cardiovascular disease (CVD)−related interventions in the U.S. population. Ten-year primary outcomes included prevalence of uncontrolled hypertension; incident myocardial infarction, stroke, CVD events, and CVD-related mortality; intervention and net medical costs by payer; productivity; and quality-adjusted life years.ResultsAbout 4.7 million (13%) fewer people with uncontrolled hypertension and 638,000 prevented cardiovascular events would be expected over 10 years. Assuming $525 per enrollee, implementation would cost payers$22.9 billion, but $25.3 billion would be saved in averted medical costs. Estimated net cost savings for Medicare approached$5.8 billion. Net costs were especially sensitive to intervention costs, with break-even thresholds of $300 (private),$450 (Medicaid), and $750 (Medicare).ConclusionsNationwide adoption of team-based care for uncontrolled hypertension could have sizable effects in reducing CVD burden. Based on the study’s assumptions, the policy would be cost saving from the perspective of Medicare and may prove to be cost effective from other payers’ perspectives. Expected net cost savings for Medicare would more than offset expected net costs for all other insurers

Persistent topology for natural data analysis - A survey

Natural data offer a hard challenge to data analysis. One set of tools is being developed by several teams to face this difficult task: Persistent topology. After a brief introduction to this theory, some applications to the analysis and classification of cells, lesions, music pieces, gait, oil and gas reservoirs, cyclones, galaxies, bones, brain connections, languages, handwritten and gestured letters are shown

New Polynomial-Based Molecular Descriptors with Low Degeneracy

In this paper, we introduce a novel graph polynomial called the ‘information polynomial’ of a graph. This graph polynomial can be derived by using a probability distribution of the vertex set. By using the zeros of the obtained polynomial, we additionally define some novel spectral descriptors. Compared with those based on computing the ordinary characteristic polynomial of a graph, we perform a numerical study using real chemical databases. We obtain that the novel descriptors do have a high discrimination power