Studying transverse volume discharge in a helium-propane mixture

The electrical properties and emission characteristics of plasma formed in a transverse volume discharge in helium-propane (He-C₆H₁₄) mixtures at a total pressure of 3–15 kPa have been studied. The spatial parameters, plasma emission spectra, and current and voltage oscillograms of the discharge, as well as the yield of carbon-containing products of propane decomposition at various pressures and compositions of the He-C₆H₁₄ gas mixture, have been determined.     

A high-power low-pressure iodine lamp pumped by glow discharge

We present the working characteristics of a high-power UV-VUV electric-discharge lamp filled with a working mixture of helium and iodine vapor (He-I₂) at a low pressure (0.1–1.5 kPa) and pumped by a dc glow discharge at a power of 15–200 W. The power of the total output UV radiation and the main emission peak at λ = 206.2 nm were studied as dependent on the electric power supplied to the glow discharge and on the partial pressure of helium in the He-I₂ mixture. The emission characteristics of the glow discharge plasma were studied in the spectral range from 200 to 350 nm. In this range, the lamp is operating predominantly on a resonance emission line of excited iodine atoms (λ = 206.2 nm, FWHM = 0.10–0.12 nm) and on a system of electronic-vibrational bands of excited iodine molecules with the main peak at λ = 342 nm. The contribution of the resonance emission due to excited iodine atoms to the total UV emission from the glow discharge plasma does not exceed 50%. The optimum partial pressure of helium is within 400–800 Pa. The total UV radiation power of the lamp operating in the optimum regime reaches 25 W at an efficiency of η ≤15%.     

Generalization to Novel Views: Universal,Class-based,and Model-based Processing

A major problem in object recognition is that a novel image of a given object can be different from all previously seen images. Images can vary considerably due to changes in viewing conditions such as viewing position and illumination. In this paper we distinguish between three types of recognition schemes by the level at which generalization to novel images takes place: universal, class, and model-based. The first is applicable equally to all objects, the second to a class of objects, and the third uses known properties of individual objects. We derive theoretical limitations on each of the three generalization levels. For the universal level, previous results have shown that no invariance can be obtained. Here we show that this limitation holds even when the assumptions made on the objects and the recognition functions are relaxed. We also extend the results to changes of illumination direction. For the class level, previous studies presented specific examples of classes of objects for which functions invariant to viewpoint exist. Here, we distinguish between classes that admit such invariance and classes that do not. We demonstrate that there is a tradeoff between the set of objects that can be discriminated by a given recognition function and the set of images from which the recognition function can recognize these objects. Furthermore, we demonstrate that although functions that are invariant to illumination direction do not exist at the universal level, when the objects are restricted to belong to a given class, an invariant function to illumination direction can be defined. A general conclusion of this study is that class-based processing, that has not been used extensively in the past, is often advantageous for dealing with variations due to viewpoint and illuminant changes.     

Phospholipid Cyclosporine Prodrugs Targeted at Inflammatory Bowel Disease (IBD) Treatment: Design,Synthesis, and in Vitro Validation

Novel phospholipid (PL)-cyclosporine conjugates were prepared and studied as potential prodrugs for inflammatory bowel disease (IBD). Our approach relies on phospholipase A₂ (PLA₂), which is overexpressed in the inflamed intestinal tissues, as the prodrug activator to potentially release cyclosporine at the site of inflammation. PL-cyclosporine prodrug conjugates with methylene linkers of various lengths between the sn-2 position of the PL and cyclosporine were synthesized and evaluated for in vitro activation. Surprisingly, despite previous work indicating that conjugates with six methylene linkers between the lipid and drug would suffer rapid enzymatic hydrolysis, with cyclosporine this was not observed. However, compounds with longer linkers (n=10, 12 methylene units) display complete release of the drug by PLA₂-catalyzed hydrolysis, thus demonstrating the importance and profound impact of structural fine-tuning. This study represents a proof-of-concept for our hypothesis and a first step towards a truly targeted IBD treatment with cyclosporine that could be administered throughout the GI tract.     

Machine learning for event selection in high energy physics

The field of high energy physics aims to discover the underlying structure of matter by searching for and studying exotic particles, such as the top quark and Higgs boson, produced in collisions at modern accelerators. Since such accelerators are extraordinarily expensive, extracting maximal information from the resulting data is essential. However, most accelerator events do not produce particles of interest, so making effective measurements requires event selection, in which events producing particles of interest (signal) are separated from events producing other particles (background). This article studies the use of machine learning to aid event selection. First, we apply supervised learning methods, which have succeeded previously in similar tasks. However, they are suboptimal in this case because they assume that the selector with the highest classification accuracy will yield the best final analysis; this is not true in practice, as such analyses are more sensitive to some backgrounds than others. Second, we present a new approach that uses stochastic optimization techniques to directly search for selectors that maximize either the precision of top quark mass measurements or the sensitivity to the presence of the Higgs boson. Empirical results confirm that stochastically optimized selectors result in substantially better analyses. We also describe a case study in which the best selector is applied to real data from the Fermilab Tevatron accelerator, resulting in the most precise top quark mass measurement of this type to date. Hence, this new approach to event selection has already contributed to our knowledge of the top quark's mass and our understanding of the larger questions upon which it sheds light.     

What Are Quantum States?

We present three strong arguments against the ontic interpretation of quantum states. We then show that the appropriate alternative is not an epistemic interpretation, but viewing quantum states as representing the available knowledge about the potentialities of a quantum system from the perspective a of a particular point in space. Unlike ordinary knowledge, which requires a knower, available knowledge can be assumed to be present regardless of a knower. The relationship between “perspectives on potentialities” and “the potentialities themselves” is clarified.