Remote sensing of changes in morphology and physiology of trees under stress

Measurements on foliage samples collected from several drought and salt treated plants revealed that leaf thickness decreased with increasing severity of the drought treatment and increased with increasing severity of treatment with NaCl, but remained essentially unaffected by treatment with CaCl2. Airborne data collected by multispectral scanner indicated that false color images provide selective enhancement of a diseased area. Comparison of simulated and actual aerial color and color IR photography revealed that the color renditions of the MSS simulations agreed closely with those of the actual photography

Remote sensing applications in forestry - Remote sensing of changes in morphology and physiology of trees under stress Annual progress report

Remote sensing of changes in morphology and physiology of trees under stres

Simulations of Spinodal Nucleation in Systems with Elastic Interactions

Systems with long-range interactions quenched into a metastable state near the pseudospinodal exhibit nucleation that is qualitatively different than the classical nucleation observed near the coexistence curve. We have observed nucleation droplets in our Langevin simulations of a two-dimensional model of martensitic transformations and have determined that the structure of the nucleating droplet differs from the stable martensite structure. Our results, together with experimental measurements of the phonon dispersion curve, allow us to predict the nature of the droplet. These results have implications for nucleation in many solid-solid transitions and the structure of the final state

Unsupervised decoding of long-term, naturalistic human neural recordings with automated video and audio annotations

Fully automated decoding of human activities and intentions from direct neural recordings is a tantalizing challenge in brain-computer interfacing. Most ongoing efforts have focused on training decoders on specific, stereotyped tasks in laboratory settings. Implementing brain-computer interfaces (BCIs) in natural settings requires adaptive strategies and scalable algorithms that require minimal supervision. Here we propose an unsupervised approach to decoding neural states from human brain recordings acquired in a naturalistic context. We demonstrate our approach on continuous long-term electrocorticographic (ECoG) data recorded over many days from the brain surface of subjects in a hospital room, with simultaneous audio and video recordings. We first discovered clusters in high-dimensional ECoG recordings and then annotated coherent clusters using speech and movement labels extracted automatically from audio and video recordings. To our knowledge, this represents the first time techniques from computer vision and speech processing have been used for natural ECoG decoding. Our results show that our unsupervised approach can discover distinct behaviors from ECoG data, including moving, speaking and resting. We verify the accuracy of our approach by comparing to manual annotations. Projecting the discovered cluster centers back onto the brain, this technique opens the door to automated functional brain mapping in natural settings

Charge Exchange Spectra of Hydrogenic and He-like Iron

We present H-like Fe XXVI and He-like Fe XXV charge-exchange spectra resulting from collisions of highly charged iron with N2 gas at an energy of 10 eV/amu in an electron beam ion trap. Although individual high-n emission lines are not resolved in our measurements, we observe that the most likely level for Fe25+ --> Fe24+ electron capture is n~9, in line with expectations, while the most likely value for Fe26+ --> Fe25+ charge exchange is significantly higher. In the Fe XXV spectrum, the K-alpha emission feature dominates, whether produced via charge exchange or collisional excitation. The K-alpha centroid is lower in energy for the former case than the latter (6666 versus 6685 eV, respectively), as expected because of the strong enhancement of emission from the forbidden and intercombination lines, relative to the resonance line, in charge-exchange spectra. In contrast, the Fe XXVI high-n Lyman lines have a summed intensity greater than that of Ly-alpha, and are substantially stronger than predicted from theoretical calculations of charge exchange with atomic H. We conclude that the angular momentum distribution resulting from electron capture using a multi-electron target gas is significantly different from that obtained with H, resulting in the observed high-n enhancement. A discussion is presented of the relevance of our results to studies of diffuse Fe emission in the Galactic Center and Galactic Ridge, particularly with ASTRO-E2/Suzaku.Comment: 16 pages, 4 figures (3 color), accepted by Ap

Bulk Band Gaps in Divalent Hexaborides

Complementary angle-resolved photoemission and bulk-sensitive k-resolved resonant inelastic x-ray scattering of divalent hexaborides reveal a >1 eV X-point gap between the valence and conduction bands, in contradiction to the band overlap assumed in several models of their novel ferromagnetism. This semiconducting gap implies that carriers detected in transport measurements arise from defects, and the measured location of the bulk Fermi level at the bottom of the conduction band implicates boron vacancies as the origin of the excess electrons. The measured band structure and X-point gap in CaB_6 additionally provide a stringent test case for proper inclusion of many-body effects in quasi-particle band calculations.Comment: 4 pages, 3 figures; new RIXS analysis; accepted for publication in PR

Coverage and Rate of Joint Communication and Parameter Estimation in Wireless Networks

From an information theoretic perspective, joint communication and sensing (JCAS) represents a natural generalization of communication network functionality. However, it requires the re-evaluation of network performance from a multi-objective perspective. We develop a novel mathematical framework for characterizing the sensing and communication coverage probability and ergodic rate in JCAS networks. We employ a formulation of sensing parameter estimation based on mutual information to extend the notions of coverage probability and ergodic rate to the radar setting. We define sensing coverage probability as the probability that the rate of information extracted about the parameters of interest associated with a typical radar target exceeds some threshold, and sensing ergodic rate as the spatial average of the aforementioned rate of information. Using this framework, we analyze the downlink sensing and communication coverage and rate of a mmWave JCAS network employing a shared waveform, directional beamforming, and monostatic sensing. Leveraging tools from stochastic geometry, we derive upper and lower bounds for these quantities. We also develop several general technical results including: i) a generic method for obtaining closed form upper and lower bounds on the Laplace Transform of a shot noise process, ii) a new analog of H{\"o}lder's Inequality to the setting of harmonic means, and iii) a relation between the Laplace and Mellin Transforms of a non-negative random variable. We use the derived bounds to numerically investigate the performance of JCAS networks under varying base station and blockage density. Among several insights, our numerical analysis indicates that network densification improves sensing SINR performance -- in contrast to communications.Comment: 87 pages, 5 figures. Published in IEEE Transactions on Information Theor