Degradation Resistant Surface Enhanced Raman Spectroscopy Substrates

Raman spectroscopy is employed by NASA, and many others, to detect trace amounts of substances. Unfortunately, the Raman signal is generally too weak to detect when very small, but non-trivial, amounts of molecules are present. One way around this weak signal is to use surface enhanced Raman spectroscopy (SERS). When used as substrates for SERS, metallic nanorods grown using physical vapor deposition (PVD) provide a large enhancement factor to the Raman signal, as much as 1012. However, Silver (Ag) nanorods that give high enhancement suffer from rapid degradation as a function of time and exposure to harsh environment. Exposure to harsh environments is an enormous issue for NASA; considering all environments experienced during space missions will be drastically different from Earth regarding atmosphere pressure, atmosphere composition, and environmental temperature. Au and Ag nanorods suffer from a thermochemical kinetic phenomenon where the surface atoms diffuse and cause the nanostructures to coalesce towards bulk structure. When in bulk, SERS enhancement is lost and the substrate becomes useless. A stable structure for SERS detection is designed through engineering the barriers to surface diffusion. Aluminum (Al) nanorods are forced to undergo surface diffusion through thermal annealing and form rough mounds with a stable terminating oxide layer. When Ag is deposited on top of this Al structure, it becomes kinetically bound and changes to physical structure become impeded. Using this paradigm, samples are grown with varied lengths of Ag and are then characterized using scanning electron microscopy (SEM) and Ultraviolet-Visible spectroscopy. The performance of the samples are then tested using SERS experiments for the detection of trace amounts of rhodamine 6G, a ‘gold standard’ analyte. Characterization shows the effectiveness of the Raman substrates remains stable up to 500°C. Transitioning to basic scientific investigation, next is to strive to isolate the individual impacts of chemical and physical changes to the Ag nanostructure and how they affect the Raman signal. Substrates are compared over the course of a month long experiment to determine the effects of vacuum storage and addressing the effects of chemical adsorbance. Additionally, this was attempted by comparing the signal degradation of Ag nanorods to that of Au, which is known to be chemically inert, allowing for the separation of chemical and physical effects. Although Ag and Au have similar melting points, Ag physically coarsened significantly more. FTIR also showed significant chemical contamination of the Ag, but not Au. A hypothesis is proposed for future investigations into the chemical changes and how they are coupled with and promote the physical changes in nanostructures. Overall, the novel SERS substrate engineered here may enable the detection of trace amounts of molecules in harsh environments and over long timescales. Conditions such as those found on space missions, where substrates will experience months or years of travel, high vacuum environments, and environments of extreme temperatures

Local Analysis of Inverse Problems: H\"{o}lder Stability and Iterative Reconstruction

We consider a class of inverse problems defined by a nonlinear map from parameter or model functions to the data. We assume that solutions exist. The space of model functions is a Banach space which is smooth and uniformly convex; however, the data space can be an arbitrary Banach space. We study sequences of parameter functions generated by a nonlinear Landweber iteration and conditions under which these strongly converge, locally, to the solutions within an appropriate distance. We express the conditions for convergence in terms of H\"{o}lder stability of the inverse maps, which ties naturally to the analysis of inverse problems

Effect of a Physical Phase Plate on Contrast Transfer in an Aberration-Corrected Transmission Electron Microscope

In this theoretical study we analyze contrast transfer of weak-phase objects in a transmission electron microscope, which is equipped with an aberration corrector (Cs-corrector) in the imaging lens system and a physical phase plate in the back focal plane of the objective lens. For a phase shift of pi/2 between scattered and unscattered electrons induced by a physical phase plate, the sine-type phase contrast transfer function is converted into a cosine-type function. Optimal imaging conditions could theoretically be achieved if the phase shifts caused by the objective lens defocus and lens aberrations would be equal zero. In reality this situation is difficult to realize because of residual aberrations and varying, non-zero local defocus values, which in general result from an uneven sample surface topography. We explore the conditions - i.e. range of Cs-values and defocus - for most favourable contrast transfer as a function of the information limit, which is only limited by the effect of partial coherence of the electron wave in Cs-corrected transmission electron microscopes. Under high-resolution operation conditions we find that a physical phase plate improves strongly low- and medium-resolution object contrast, while improving tolerance to defocus and Cs-variations, compared to a microscope without a phase plate

Controlling Complex Langevin simulations of lattice models by boundary term analysis

One reason for the well known fact that the Complex Langevin (CL) method sometimes fails to converge or converges to the wrong limit has been identified long ago: it is insufficient decay of the probability density either near infinity or near poles of the drift, leading to boundary terms that spoil the formal argument for correctness. To gain a deeper understanding of this phenomenon, in a previous paper we have studied the emergence of such boundary terms thoroughly in a simple model, where analytic results can be compared with numerics. Here we continue this type of analysis for more physically interesting models, focusing on the boundaries at infinity. We start with abelian and non-abelian one-plaquette models, then we proceed to a Polyakov chain model and finally to high density QCD (HDQCD) and the 3D XY model. We show that the direct estimation of the systematic error of the CL method using boundary terms is in principle possible.Comment: 17 pages, 11 figure

Survival of gastrointestinal stromal tumor patients in the imatinib era: life raft group observational registry

<p>Abstract</p> <p>Background</p> <p>Gastrointestinal stromal tumors (GIST), one of the most common mesenchymal tumors of the gastrointestinal tract, prior to routine immunohistochemical staining and the introduction of tyrosine kinase inhibitors, were often mistaken for neoplasms of smooth muscle origin such as leiomyomas, leiomyosarcomas or leiomyoblastomas. Since the advent of imatinib, GIST has been further delineated into adult- (KIT or PDGFRα mutations) and pediatric- (typified by wild-type GIST/succinate dehydrogenase deficiencies) types. Using varying gender ratios at age of diagnosis we sought to elucidate prognostic factors for each sub-type and their impact on overall survival.</p> <p>Methods</p> <p>This is a long-term retrospective analysis of a large observational study of an international open cohort of patients from a GIST research and patient advocacy's lifetime registry. Demographic and disease-specific data were voluntarily supplied by its members from May 2000-October 2010; the primary outcome was overall survival. Associations between survival and prognostic factors were evaluated by univariate Cox proportional hazard analyses, with backward selection at <it>P </it>< 0.05 used to identify independent factors.</p> <p>Results</p> <p>Inflections in gender ratios by age at diagnosis in years delineated two distinct groups: above and below age 35 at diagnosis. Closer analysis confirmed the above 35 age group as previously reported for adult-type GIST, typified by mixed primary tumor sites and gender, KIT or PDGFRα mutations, and shorter survival times. The pediatric group (< age 18 at diagnosis) was also as previously reported with predominantly stomach tumors, females, wild-type GIST or SDH mutations, and extended survival. "Young adults" however formed a third group aged 18-35 at diagnosis, and were a clear mix of these two previously reported distinct sub-types.</p> <p>Conclusions</p> <p>Pediatric- and adult-type GIST have been previously characterized in clinical settings and these observations confirm significant prognostic factors for each from a diverse real-world cohort. Additionally, these findings suggest that extra diligence be taken with "young adults" (aged 18-35 at diagnosis) as pediatric-type GIST may present well beyond adolescence, particularly as these distinct sub-types have different causes, and consequently respond differently to treatments.</p

Regularization of Linear Ill-posed Problems by the Augmented Lagrangian Method and Variational Inequalities

We study the application of the Augmented Lagrangian Method to the solution of linear ill-posed problems. Previously, linear convergence rates with respect to the Bregman distance have been derived under the classical assumption of a standard source condition. Using the method of variational inequalities, we extend these results in this paper to convergence rates of lower order, both for the case of an a priori parameter choice and an a posteriori choice based on Morozov's discrepancy principle. In addition, our approach allows the derivation of convergence rates with respect to distance measures different from the Bregman distance. As a particular application, we consider sparsity promoting regularization, where we derive a range of convergence rates with respect to the norm under the assumption of restricted injectivity in conjunction with generalized source conditions of H\"older type

Sparse Regularization with lql^q Penalty Term

We consider the stable approximation of sparse solutions to non-linear operator equations by means of Tikhonov regularization with a subquadratic penalty term. Imposing certain assumptions, which for a linear operator are equivalent to the standard range condition, we derive the usual convergence rate $O(\sqrt{\delta})$ of the regularized solutions in dependence of the noise level $\delta$. Particular emphasis lies on the case, where the true solution is known to have a sparse representation in a given basis. In this case, if the differential of the operator satisfies a certain injectivity condition, we can show that the actual convergence rate improves up to $O(\delta)$.Comment: 15 page

Towards Innovative Solutions through Integrative Futures Analysis - Preliminary qualitative scenarios

This report presents preliminary results of developing qualitative global water scenarios. The water scenarios are developed to be consistent with the underlying Shared Socio- Economic Pathways (SSPs). In this way different stakeholders in different contexts (climate, water) can be presented with consistent set of scenarios avoiding confusion and increasing policy impact. Water scenarios are based on the conceptual framework that has been developd specifically for this effort. The framework provides clear representation of important dimensions in the areas of Nature, Economy and Society and Water dimensions that are embedded in them. These critical dimensions are used to describe future changes in a consistent way for all scenarios. Three scenarios are presented based on SSP1, SSP2 and SSP3 respectively. Hydro-economic classes are introduced to further differentiate within scenarios based on economic and water conditions for specific regions and/or countries. In the process of building these preliminary water scenarios assumptions that are presented in this report, the number of challenges have been met. In the conclusions section these challenges are summarized and possible ways of tackling them are described

Iteratively regularized Newton-type methods for general data misfit functionals and applications to Poisson data

We study Newton type methods for inverse problems described by nonlinear operator equations $F(u)=g$ in Banach spaces where the Newton equations $F'(u_n;u_{n+1}-u_n) = g-F(u_n)$ are regularized variationally using a general data misfit functional and a convex regularization term. This generalizes the well-known iteratively regularized Gauss-Newton method (IRGNM). We prove convergence and convergence rates as the noise level tends to 0 both for an a priori stopping rule and for a Lepski{\u\i}-type a posteriori stopping rule. Our analysis includes previous order optimal convergence rate results for the IRGNM as special cases. The main focus of this paper is on inverse problems with Poisson data where the natural data misfit functional is given by the Kullback-Leibler divergence. Two examples of such problems are discussed in detail: an inverse obstacle scattering problem with amplitude data of the far-field pattern and a phase retrieval problem. The performence of the proposed method for these problems is illustrated in numerical examples