Improved analytic longitudinal response analysis for axisymmetric launch vehicles. Volume II - Computer program description

Improved analytic longitudinal response analysis for axisymmetric launch vehicles - computer program descriptio

Spitzer reveals what's behind Orion's Bar

We present Spitzer Space Telescope observations of 11 regions SE of the Bright Bar in the Orion Nebula, along a radial from the exciting star theta1OriC, extending from 2.6 to 12.1'. Our Cycle 5 programme obtained deep spectra with matching IRS short-high (SH) and long-high (LH) aperture grid patterns. Most previous IR missions observed only the inner few arcmin. Orion is the benchmark for studies of the ISM particularly for elemental abundances. Spitzer observations provide a unique perspective on the Ne and S abundances by virtue of observing the dominant ionization states of Ne (Ne+, Ne++) and S (S++, S3+) in Orion and H II regions in general. The Ne/H abundance ratio is especially well determined, with a value of (1.01+/-0.08)E-4. We obtained corresponding new ground-based spectra at CTIO. These optical data are used to estimate the electron temperature, electron density, optical extinction, and the S+/S++ ratio at each of our Spitzer positions. That permits an adjustment for the total gas-phase S abundance because no S+ line is observed by Spitzer. The gas-phase S/H abundance ratio is (7.68+/-0.30)E-6. The Ne/S abundance ratio may be determined even when the weaker hydrogen line, H(7-6) here, is not measured. The mean value, adjusted for the optical S+/S++ ratio, is Ne/S = 13.0+/-0.6. We derive the electron density versus distance from theta1OriC for [S III] and [S II]. Both distributions are for the most part decreasing with increasing distance. A dramatic find is the presence of high-ionization Ne++ all the way to the outer optical boundary ~12' from theta1OriC. This IR result is robust, whereas the optical evidence from observations of high-ionization species (e.g. O++) at the outer optical boundary suffers uncertainty because of scattering of emission from the much brighter inner Huygens Region.Comment: 60 pages, 16 figures, 10 tables. MNRAS accepte

Preference-for-Solitude and Adjustment Difficulties in Early and Late Adolescence

Social withdrawal has been associated with adjustment difficulties across development. Although much is known about shyness, little is known about preference-for-solitude; even less is known about its relations with adjustment across different periods of adolescence. We examined whether preference-for-solitude might be differentially associated with adjustment difficulties in early and late adolescence. Self- and parent-reports of withdrawal motivations and adjustment were collected from 234 eighth graders (113 boys; M age = 13.43) and 204 twelfth graders (91 boys; M age = 17.25). Results from structural equation modeling demonstrated that above and beyond the effects of shyness, preference-for-solitude was more strongly associated with adjustment difficulties in 8th grade than in 12th grade. Preference-for-solitude was associated with greater anxiety/depression, emotion dysregulation, and lower self-esteem in 8th grade; these relations were not found in 12th grade. Although preference-for-solitude was associated with lower social competence in both 8th and 12th grades, this relation was significantly stronger in 8th grade than in 12th grade. Findings suggest preference-for-solitude has closer ties to maladjustment in early adolescence than in late adolescence. Interventions targeting preferred-solitary youth in early adolescence may be particularly fruitfu

Statistical inference optimized with respect to the observed sample for single or multiple comparisons

The normalized maximum likelihood (NML) is a recent penalized likelihood that has properties that justify defining the amount of discrimination information (DI) in the data supporting an alternative hypothesis over a null hypothesis as the logarithm of an NML ratio, namely, the alternative hypothesis NML divided by the null hypothesis NML. The resulting DI, like the Bayes factor but unlike the p-value, measures the strength of evidence for an alternative hypothesis over a null hypothesis such that the probability of misleading evidence vanishes asymptotically under weak regularity conditions and such that evidence can support a simple null hypothesis. Unlike the Bayes factor, the DI does not require a prior distribution and is minimax optimal in a sense that does not involve averaging over outcomes that did not occur. Replacing a (possibly pseudo-) likelihood function with its weighted counterpart extends the scope of the DI to models for which the unweighted NML is undefined. The likelihood weights leverage side information, either in data associated with comparisons other than the comparison at hand or in the parameter value of a simple null hypothesis. Two case studies, one involving multiple populations and the other involving multiple biological features, indicate that the DI is robust to the type of side information used when that information is assigned the weight of a single observation. Such robustness suggests that very little adjustment for multiple comparisons is warranted if the sample size is at least moderate.Comment: Typo in equation (7) of v2 corrected in equation (6) of v3; clarity improve

Tailoring inputs to achieve maximal neuronal firing

We consider the constrained optimization of excitatory synaptic input patterns to maximize spike generation in leaky integrate-and-fire (LIF) and theta model neurons. In the case of discrete input kicks with a fixed total magnitude, optimal input timings and strengths are identified for each model using phase plane arguments. In both cases, optimal features relate to finding an input level at which the drop in input between successive spikes is minimized. A bounded minimizing level always exists in the theta model and may or may not exist in the LIF model, depending on parameter tuning. We also provide analytical formulas to estimate the number of spikes resulting from a given input train. In a second case of continuous inputs of fixed total magnitude, we analyze the tuning of an input shape parameter to maximize the number of spikes occurring in a fixed time interval. Results are obtained using numerical solution of a variational boundary value problem that we derive, as well as analysis, for the theta model and using a combination of simulation and analysis for the LIF model. In particular, consistent with the discrete case, the number of spikes in the theta model rises and then falls again as the input becomes more tightly peaked. Under a similar variation in the LIF case, we numerically show that the number of spikes increases monotonically up to some bound and we analytically constrain the times at which spikes can occur and estimate the bound on the number of spikes fired