The Conductor-Dielectric Junctions in a Low Density Plasma

A conductor-dielectric junction exposed to the space environment is a frequent spacecraft design feature. Due to spacecraft charging and/or solar array operation, the conductor can acquire a high potential with respect to the surrounding plasma. If this potential is positive the insulators adjacent to exposed conductors can collect current as if they were conductors themselves. This phenomenon, called snapover, results in a substantial increase in current collection, and may even result in a glow discharge if the potential is high enough. If a conductor has a negative potential, arcing can occur at the site of a junction. Both of these phenomena negatively affect spacecraft operation. To prevent negative consequences, the physical mechanisms of snapover and arc inception require investigation. In this paper, results are presented of an experimental and theoretical study of snapover, glow discharge, and arc phenomena for different materials immersed in argon or xenon plasmas. The effect of snapover is investigated for several metal-dielectric junctions: copper-teflon, copper-Kapton, copper-glass, aluminum-teflon, aluminum-Kapton, steelteflon, anodized aluminum with pinholes, and copper-ceramics. I-V curves are measured and snapover inception voltages, essential parameters (increase in current and collection area due to secondary electrons), and glow discharge inception thresholds are determined. Optical spectra are obtained for glow discharges in both argon and xenon plasmas. These spectra provide information regarding atomic species entrapped in the glow region. Some spectral lines can be used to estimate plasma parameters in the discharge area. A videocamera and linear array were used to confirm that snapover inception is accompanied by very low intensity visible light emission. This result seems to be important for the estimate of the light pollution around spacecraft. Optical spectra (wavelengths 380-650 nm) of arcs are also obtained on a negatively biased chromic acid anodized aluminum plate immersed in low density argon and xenon plasmas. Analysis of these spectra confirms our earlier findings that aluminum atoms are ejected from the arc site. Moreover, it is found that chromium atoms are also quite abundant in the arc plasma. It is believed that the latter results contribute considerably to the understanding of processes of plasma contamination caused by arcing

Characterizing and mapping cropping patterns in a complex agro-ecosystem: An iterative participatory mapping procedure using machine learning algorithms and MODIS vegetation indices

Accurate and up-to-date spatial agricultural information is essential for applications including agro-environmental assessment, crop management, and appropriate targeting of agricultural technologies. There is growing research interest in spatial analysis of agricultural ecosystems applying satellite remote sensing technologies. However, usability of information generated from many of remotely sensed data is often constrained by accuracy problems. This is of particular concern in mapping complex agro-ecosystems in countries where small farm holdings are dominated by diverse crop types. This study is a contribution to the ongoing efforts towards overcoming accuracy challenges faced in remote sensing of agricultural ecosystems. We applied time-series analysis of vegetation indices (Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI)) derived from the Moderate Resolution Imaging Spectrometer (MODIS) sensor to detect seasonal patterns of irrigated and rainfed cropping patterns in five townships in the Central Dry Zone of Myanmar, which is an important agricultural region of the country has been poorly mapped with respect to cropping practices. To improve mapping accuracy and map legend completeness, we implemented a combination of (i) an iterative participatory approach to field data collection and classification, (ii) the identification of appropriate size and types of predictor variables (VIs), and (iii) evaluation of the suitability of three Machine Learning algorithms: Support Vector Machine (SVM), Random Forest (RF), and C5.0 algorithms under varying training sample sizes. Through these procedures, we were able to progressively improve accuracy and achieve maximum overall accuracy of 95% When a small sized training dataset was used, accuracy achieved by RF was significantly higher compared to SVM and C5.0 (P < 0.01), but as sample size increased, accuracy differences among the three machine learning algorithms diminished. Accuracy achieved by use of NDVI was consistently better than that of EVI (P < 0.01). The maximum overall accuracy was achieved using RF and 8-days NDVI composites for three years of remote sensing data. In conclusion, our findings highlight the important role of participatory classification, especially in areas where cropping systems are highly diverse and differ over space and time. We also show that the choice of classifiers and size of predictor variables are essential and complementary to the participatory mapping approach in achieving desired accuracy of cropping pattern mapping in areas where other sources of spatial information are scarce

Experimental control of single-mode laser chaos by using continuous, time-delayed feedback

Control of chaos in the single-mode optically pumped far-infrared (NH3)-N-15 laser is experimentally demonstrated using continuous time-delay control. Both the Lorenz spiral chaos and the detuned period-doubling chaos exhibited by the laser have been controlled. While the laser is in the Lorenz spiral chaos regime the chaos has been controlled both such that the laser output is cw, with corrections of only a fraction of a percent necessary to keep it there, and to period one. The laser has also been controlled while in the period-doubling chaos regime, to both the period-one and -two states

Dependence of transient dynamics in a class-C laser upon variation of inversion with time

The transient statistics of a gain-switched coherently pumped class-C laser displays a linear correlation between the first passage time and subsequent peak intensity. Measurements are reported showing a positive or negative sign of this linear correlation, controlled through the switching time and the laser detuning. Further measurements of the small-signal laser gain combined with calculations involving a three-level laser model indicate that this sign fundamentally depends upon the way the laser inversion varies during the gain switching, despite the added dynamics of the laser polarization in the class-C laser. [S1050-2947(97)07112-6]

Understanding the treatment benefit of hyperimmune anti-influenza intravenous immunoglobulin (Flu-IVIG) for severe human influenza

Background: Antibody-based therapies for respiratory viruses are of increasing importance. The INSIGHT 006 trial administered anti-influenza hyperimmune intravenous immunoglobulin (Flu-IVIG) to patients hospitalized with influenza. Flu-IVIG treatment improved outcomes in patients with influenza B but showed no benefit for influenza A. Methods: To probe potential mechanisms of Flu-IVIG utility, sera collected from patients hospitalized with influenza A or B viruses (IAV or IBV) were analyzed for antibody isotype/subclass and Fcγ receptor (FcγR) binding by ELISA, bead-based multiplex, and NK cell activation assays. Results: Influenza-specific FcγR-binding antibodies were elevated in Flu-IVIG–infused IBV- and IAV-infected patients. In IBV-infected participants (n = 62), increased IgG3 and FcγR binding were associated with more favorable outcomes. Flu-IVIG therapy also improved the odds of a more favorable outcome in patients with low levels of anti-IBV Fc-functional antibody. Higher FcγR-binding antibody was associated with less favorable outcomes in IAV-infected patients (n = 50), and Flu-IVIG worsened the odds of a favorable outcome in participants with low levels of anti-IAV Fc-functional antibody. Conclusion: These detailed serological analyses provide insights into antibody features and mechanisms required for a successful humoral response against influenza, suggesting that IBV-specific, but not IAV-specific, antibodies with Fc-mediated functions may assist in improving influenza outcome. This work will inform development of improved influenza immunotherapies

Design principles for riboswitch function

Scientific and technological advances that enable the tuning of integrated regulatory components to match network and system requirements are critical to reliably control the function of biological systems. RNA provides a promising building block for the construction of tunable regulatory components based on its rich regulatory capacity and our current understanding of the sequence–function relationship. One prominent example of RNA-based regulatory components is riboswitches, genetic elements that mediate ligand control of gene expression through diverse regulatory mechanisms. While characterization of natural and synthetic riboswitches has revealed that riboswitch function can be modulated through sequence alteration, no quantitative frameworks exist to investigate or guide riboswitch tuning. Here, we combined mathematical modeling and experimental approaches to investigate the relationship between riboswitch function and performance. Model results demonstrated that the competition between reversible and irreversible rate constants dictates performance for different regulatory mechanisms. We also found that practical system restrictions, such as an upper limit on ligand concentration, can significantly alter the requirements for riboswitch performance, necessitating alternative tuning strategies. Previous experimental data for natural and synthetic riboswitches as well as experiments conducted in this work support model predictions. From our results, we developed a set of general design principles for synthetic riboswitches. Our results also provide a foundation from which to investigate how natural riboswitches are tuned to meet systems-level regulatory demands

Strangeness nuclear physics: a critical review on selected topics

Selected topics in strangeness nuclear physics are critically reviewed. This includes production, structure and weak decay of $\Lambda$--Hypernuclei, the $\bar K$ nuclear interaction and the possible existence of $\bar K$ bound states in nuclei. Perspectives for future studies on these issues are also outlined.Comment: 63 pages, 51 figures, accepted for publication on European Physical Journal

Enhancing the immunogenicity of tumour lysate-loaded dendritic cell vaccines by conjugation to virus-like particles

BACKGROUND: Tumour cell lysates are an excellent source of many defined and undefined tumour antigens and have been used clinically in immunotherapeutic regimes but with limited success. METHODS: We conjugated Mel888 melanoma lysates to rabbit haemorrhagic disease virus virus-like particles (VLP), which can act as vehicles to deliver multiple tumour epitopes to dendritic cells (DC) to effectively activate antitumour responses. RESULTS: Virus-like particles did not stimulate the phenotypic maturation of DC although, the conjugation of lysates to VLP (VLP-lysate) did overcome lysate-induced suppression of DC activation. Lysate-conjugated VLP enhanced delivery of antigenic proteins to DC, while the co-delivery of VLP-lysates with OK432 resulted in cross-priming of naïve T cells, with expansion of a MART1(+) population of CD8(+) T cells and generation of a specific cytotoxic response against Mel888 tumour cell targets. The responses generated with VLP-lysate and OK432 were superior to those stimulated by unconjugated lysate with OK432. CONCLUSION: Collectively, these results show that the combination of VLP-lysate with OK432 delivered to DC overcomes the suppressive effects of lysates, and enables priming of naïve T cells with superior ability to specifically kill their target tumour cells

Design Principles for Ligand-Sensing, Conformation-Switching Ribozymes

Nucleic acid sensor elements are proving increasingly useful in biotechnology and biomedical applications. A number of ligand-sensing, conformational-switching ribozymes (also known as allosteric ribozymes or aptazymes) have been generated by some combination of directed evolution or rational design. Such sensor elements typically fuse a molecular recognition domain (aptamer) with a catalytic signal generator (ribozyme). Although the rational design of aptazymes has begun to be explored, the relationships between the thermodynamics of aptazyme conformational changes and aptazyme performance in vitro and in vivo have not been examined in a quantitative framework. We have therefore developed a quantitative and predictive model for aptazymes as biosensors in vitro and as riboswitches in vivo. In the process, we have identified key relationships (or dimensionless parameters) that dictate aptazyme performance, and in consequence, established equations for precisely engineering aptazyme function. In particular, our analysis quantifies the intrinsic trade-off between ligand sensitivity and the dynamic range of activity. We were also able to determine how in vivo parameters, such as mRNA degradation rates, impact the design and function of aptazymes when used as riboswitches. Using this theoretical framework we were able to achieve quantitative agreement between our models and published data. In consequence, we are able to suggest experimental guidelines for quantitatively predicting the performance of aptazyme-based riboswitches. By identifying factors that limit the performance of previously published systems we were able to generate immediately testable hypotheses for their improvement. The robust theoretical framework and identified optimization parameters should now enable the precision design of aptazymes for biotechnological and clinical applications