Exploiting Structural Complexity for Robust and Rapid Hyperspectral Imaging

This paper presents several strategies for spectral de-noising of hyperspectral images and hypercube reconstruction from a limited number of tomographic measurements. In particular we show that the non-noisy spectral data, when stacked across the spectral dimension, exhibits low-rank. On the other hand, under the same representation, the spectral noise exhibits a banded structure. Motivated by this we show that the de-noised spectral data and the unknown spectral noise and the respective bands can be simultaneously estimated through the use of a low-rank and simultaneous sparse minimization operation without prior knowledge of the noisy bands. This result is novel for for hyperspectral imaging applications. In addition, we show that imaging for the Computed Tomography Imaging Systems (CTIS) can be improved under limited angle tomography by using low-rank penalization. For both of these cases we exploit the recent results in the theory of low-rank matrix completion using nuclear norm minimization

Improved prediction of laminar leading edge separation

Research was conducted to provide a definite criterion for the prediction of the bubble burst on airfoils typical of those used for fighter wings. The approach taken was to correlate existing airfoil bubble burst data using various parameters at the laminar separation point. The method due to Weber was modified to provide a continuous analytic solution for the velocity distribution around the airfoil leading edge. Coupling the modified Weber method with the Stratford laminar separation prediction method leads to a universal chart giving the conditions at separation as a function of stagnation location and leading edge radius. Application of the combined method to available two-dimensional airfoil data resulted in an empirical criterion presenting the limiting local velocity gradient at separation as a function of the boundary layer momentum thickness at separation for bubble burst. The correlation leads as well to the qualitative explanation of two types of laminar stall: thin airfoil and leading edge. The validity of the correlation is demonstrated by predicting the lift coefficient and angle of attack for stall on airfoils with leading edge or trailing edge flaps

Common learning

Consider two agents who learn the value of an unknown parameter by observing a sequence of private signals. The signals are independent and identically distributed across time but not necessarily across agents. We show that when each agent's signal space is finite, the agents will commonly learn the value of the parameter, that is, that the true value of the parameter will become approximate common knowledge. The essential step in this argument is to express the expectation of one agent's signals, conditional on those of the other agent, in terms of a Markov chain. This allows us to invoke a contraction mapping principle ensuring that if one agent's signals are close to those expected under a particular value of the parameter, then that agent expects the other agent's signals to be even closer to those expected under the parameter value. In contrast, if the agents' observations come from a countably infinite signal space, then this contraction mapping property fails. We show by example that common learning can fail in this case

How Has McDonnell Affected Prosecutors’ Ability to Police Public Corruption? What Are Politicians And Lobbyists Allowed To Do, And What Are Prosecutors Able To Prosecute?

The question posed to the panelists on the first panel is: How has McDonnell affected prosecutors’ ability to police public corruption? What can politicians and lobbyists do and what can prosecutors prosecute

Relative Entailment Among Probabilistic Implications

We study a natural variant of the implicational fragment of propositional logic. Its formulas are pairs of conjunctions of positive literals, related together by an implicational-like connective; the semantics of this sort of implication is defined in terms of a threshold on a conditional probability of the consequent, given the antecedent: we are dealing with what the data analysis community calls confidence of partial implications or association rules. Existing studies of redundancy among these partial implications have characterized so far only entailment from one premise and entailment from two premises, both in the stand-alone case and in the case of presence of additional classical implications (this is what we call "relative entailment"). By exploiting a previously noted alternative view of the entailment in terms of linear programming duality, we characterize exactly the cases of entailment from arbitrary numbers of premises, again both in the stand-alone case and in the case of presence of additional classical implications. As a result, we obtain decision algorithms of better complexity; additionally, for each potential case of entailment, we identify a critical confidence threshold and show that it is, actually, intrinsic to each set of premises and antecedent of the conclusion

A Glimpse into Secondary Students’ Understanding of Functions

In this article we examine how secondary school students think about functional relationships. More specifically, we examined seven students’ intuitive knowledge in regards to representing two real-world situations with functions. We found students do not tend to represent functional relationships with coordinate graphs even though they are able to do so. Instead, these students tend to represent the physical characteristics of the situation. In addition, we discovered that middleschool students had sophisticated ideas of dependency and covariance. All the students were able to use their models of the situation to generalize and make predictions. These findings suggest that secondary students have the ability to describe covariant and dependent relations and that their models of functions tend to be more intuitive than mathematical-even for the students in algebra II and calculus. Our work suggests a possible framework that begins describing a way of analyzing students’ understanding of functions

Costs of Inaction on Maternal Mortality: Qualitative Evidence of the Impacts of Maternal Deaths on Living Children in Tanzania.

Little is known about the interconnectedness of maternal deaths and impacts on children, beyond infants, or the mechanisms through which this interconnectedness is established. A study was conducted in rural Tanzania to provide qualitative insight regarding how maternal mortality affects index as well as other living children and to identify shared structural and social factors that foster high levels of maternal mortality and child vulnerabilities. Adult family members of women who died due to maternal causes (N = 45) and key stakeholders (N = 35) participated in in-depth interviews. Twelve focus group discussions were also conducted (N = 83) among community leaders in three rural regions of Tanzania. Findings highlight the widespread impact of a woman's death on her children's health, education, and economic status, and, by inference, the roles that women play within their families in rural Tanzanian communities. The full costs of failing to address preventable maternal mortality include intergenerational impacts on the nutritional status, health, and education of children, as well as the economic capacity of families. When setting priorities in a resource-poor, high maternal mortality country, such as Tanzania, the far-reaching effects that reducing maternal deaths can have on families and communities, as well as women's own lives, should be considered

The rise of an ionized wind in the Narrow Line Seyfert 1 Galaxy Mrk 335 observed by XMM-Newton and HST

We present the discovery of an outflowing ionized wind in the Seyfert 1 Galaxy Mrk 335. Despite having been extensively observed by most of the largest X-ray observatories in the last decade, this bright source was not known to host warm absorber gas until recent XMM-Newton observations in combination with a long-term Swift monitoring program have shown extreme flux and spectral variability. High resolution spectra obtained by the XMM-Newton RGS detector reveal that the wind consists of three distinct ionization components, all outflowing at a velocity of 5000 km/s. This wind is clearly revealed when the source is observed at an intermediate flux state (2-5e-12 ergs cm^-2 s^-1). The analysis of multi-epoch RGS spectra allowed us to compare the absorber properties at three very different flux states of the source. No correlation between the warm absorber variability and the X-ray flux has been determined. The two higher ionization components of the gas may be consistent with photoionization equilibrium, but we can exclude this for the only ionization component that is consistently present in all flux states (log(xi)~1.8). We have included archival, non-simultaneous UV data from HST (FOS, STIS, COS) with the aim of searching for any signature of absorption in this source that so far was known for being absorption-free in the UV band. In the COS spectra obtained a few months after the X-ray observations we found broad absorption in CIV lines intrinsic to the AGN and blueshifted by a velocity roughly comparable to the X-ray outflow. The global behavior of the gas in both bands can be explained by variation of the covering factor and/or column density, possibly due to transverse motion of absorbing clouds moving out of the line of sight at Broad Line Region scale.Comment: 24 pages, 12 figures, ApJ accepte

High rate continuous synthesis of nanocrystalline materials in a colliding vapor stream of microdroplets

Progress in nanotechnology is driving the need of large scale synthesis of functional nanomaterials. The lack of a workforce trained on process control and scale-up of nanomaterials manufacturing, the gap between laboratories and economically practical nanofabrication and the funding strain on the survivability of startup companies all contribute to the difficulties in scaling up nanotechnologies and their commercialization [1,2]. We report here a high rate continuous synthesis of functional inorganic nanomaterials using colliding vapor stream of reagents microdroplets