Direct sampling of chemical weapons in water by photoionization mass spectrometry

The vulnerability of water supplies to toxic contamination calls for fast and effective means for screening water samples for multiple threats. We describe the use of photoionization (PI) mass spectrometry (MS) for high-speed, high-throughput screening and molecular identification of chemical weapons (CW) threats and other hazardous compounds. The screening technology can detect a wide range of compounds at subacute concentrations with no sample preparation and a sampling cycle time of approximately 45 s. The technology was tested with CW agents VX, GA, GB, GD, GF, HD, HN1, and HN3, in addition to riot agents and precursors. All are sensitively detected and give simple PI mass spectra dominated by the parent ion. The target application of the PI MS method is as a routine, real-time early warning system for CW agents and other hazardous compounds in air and in water. In this work, we also present comprehensive measurements for water analysis and report on the system detection limits, linearity, quantitation accuracy, and false positive (FP) and false negative rates for concentrations at subacute levels. The latter data are presented in the form of receiver operating characteristic curves of the form of detection probability P(D) versus FP probability P(FP). These measurements were made using the CW surrogate compounds, DMMP, DEMP, DEEP, and DIMP. Method detection limits (3sigma) obtained using a capillary injection method yielded 1, 6, 3, and 2 ng/mL, respectively. These results were obtained using 1-microL injections of water samples without any preparation, corresponding to mass detection limits of 1, 6, 3, and 2 pg, respectively. The linear range was about 3-4 decades and the dynamic range about 4-5 decades. The relative standard deviations were generally <10% at CW subacute concentrations levels.     

Engineering metal-impurity nanodefects for low-cost solar cells

As the demand for high-quality solar-cell feedstock exceeds supply and drives prices upwards, cheaper but dirtier alternative feedstock materials are being developed. Successful use of these alternative feedstocks requires that one rigorously control the deleterious effects of the more abundant metallic impurities. In this study, we demonstrate how metal nanodefect engineering can be used to reduce the electrical activity of metallic impurities, resulting in dramatic enhancements of performance even in heavily contaminated solar-cell material. Highly sensitive synchrotron-based measurements directly confirm that the spatial and size distributions of metal nanodefects regulate the minority-carrier diffusion length, a key parameter for determining the actual performance of solar-cell devices. By engineering the distributions of metal-impurity nanodefects in a controlled fashion, the minority-carrier diffusion length can be increased by up to a factor of four, indicating that the use of lower-quality feedstocks with proper controls may be a viable alternative to producing cost-effective solar cells.     

Nonlinear control techniques for an atomic force microscope system

Two nonlinear control techniques are proposed for an atomic force microscope system. Initially, a learning-based control algorithm is developed for the microcantilever-sample system that achieves asymptotic cantilever tip tracking for periodic trajectories. Specifically, the control approach utilizes a learning-based feedforward term to compensate for periodic dynamics and high-gain terms to account for non-periodic dynamics. An adaptive control algorithm is then developed to achieve asymptotic cantilever tip tracking for bounded tip trajectories despite uncertainty throughout the system parameters. Simulation results are provided to illttstrate the efficacy and performance of the control strategies.     

Tumor-Localized Administration of α-GalCer to Recruit Invariant Natural Killer T Cells and Enhance Their Antitumor Activity against Solid Tumors

Invariant natural killer T (iNKT) cells have the capacity to mount potent anti-tumor reactivity and have therefore become a focus in the development of cell-based immunotherapy. iNKT cells attack tumor cells using multiple mechanisms with a high efficacy; however, their clinical application has been limited because of their low numbers in cancer patients and difficulties in infiltrating solid tumors. In this study, we aimed to overcome these critical limitations by using α-GalCer, a synthetic glycolipid ligand specifically activating iNKT cells, to recruit iNKT to solid tumors. By adoptively transferring human iNKT cells into tumor-bearing humanized NSG mice and administering a single dose of tumor-localized α-GalCer, we demonstrated the rapid recruitment of human iNKT cells into solid tumors in as little as one day and a significantly enhanced tumor killing ability. Using firefly luciferase-labeled iNKT cells, we monitored the tissue biodistribution and pharmacokinetics/pharmacodynamics (PK/PD) of human iNKT cells in tumor-bearing NSG mice. Collectively, these preclinical studies demonstrate the promise of an αGC-driven iNKT cell-based immunotherapy to target solid tumors with higher efficacy and precision.     

Green leaf phenology at Landsat resolution: Scaling from the field to the satellite

Despite the large number of in situ, plot-level phenological measurements and satellite-derived phenological studies, there has been little success to date in merging these records temporally or spatially. In this research, we bridge this scale gap through higher resolution satellite records (Landsat) and quantify the accuracy of satellite-derived metrics with direct field measurements. We compiled fifty-seven Landsat scenes from southern New England (P12 R51) from 1984 to 2002. Green vegetation areal abundance for each scene was derived from spectral mixture analysis and a single set of endmembers. The leaf area signal was fit with a logistic-growth simulating sigmoid curve to derive phenological markers (half-maximum leaf-onset and offset). Spring leaf-onset dates in homogenous stands of deciduous forests displayed significant and persistent local variability. The local variability was validated with multiple springtime ground observations (r² = 0.91). The highest degree of verified small-scale variation occurred where contiguous forests displayed leaf-onset gradients of 10-14 days over short distances (< 500 m). These dramatic gradients occur in of low-relief (< 40 m) upland regions. The patterns suggest that microclimates resulting from springtime cold-air drainage may be influential in governing the start of leaf growth; every 4.16 m loss in elevation delayed spring leaf onset by 1 day. These microclimates may be of crucial importance in interpreting in situ records and interpolating phenology from satellite data. Regional patterns from the Landsat analyses suggest topographic, coastal, and land-use controls on phenology. Our results indicate that deciduous forests in the Providence, RI metropolitan area leaf out 5-7 days earlier than comparable rural areas. The platform-independent curve-fit methodology may be extended across platforms and field data. The methodologically consistent approach, in tandem with Landsat data, allows an effective scaling from plot to satellite phenological observations.     

Analysis of input-to-state stability for discrete time nonlinear systems via dynamic programming

The input-to-state stability (ISS) property for systems with disturbances has received considerable attention over the past decade or so, with many applications and characterizations reported in the literature. The main purpose of this paper is to present analysis results for ISS that utilize dynamic programming techniques to characterize minimal ISS gains and transient bounds. These characterizations naturally lead to computable necessary and sufficient conditions for ISS. Our results make a connection between ISS and optimization problems in nonlinear dissipative systems theory (including L₂-gain analysis and nonlinear H_∞ theory). As such, the results presented address an obvious gap in the literature.     

The Synchronous Approach to Designing Reactive Systems

Synchronous programming is available through several formally defined languages having very different characteristics: Esterel is imperative, while Lustre and Signal are declarative in style; Statecharts and Argos are graphical languages that allow one to program by constructing hierarchical automata. Our motivation for taking the synchronous design paradigm further, integrating imperative, declarative (or dataflow), and graphical programming styles, is that real systems typically have components that match each of these profiles. This paper motivates our interest in the mixed language programming of embedded software around a number of examples, and sketches the semantical foundation of the Synchronie toolset which ensures a coherent computational model. This toolset supports a design trajectory that incorporates rapid prototyping and systematic testing for early design validation, an object oriented development methodology for long term software management, and formal verification at the level of automatically generated object code.