Eglin Air Force Base

Imaging polarimetry has emerged over the past three decades as a powerful tool to enhance the information available in a variety of remote sensing applications. We discuss the foundations of passive imaging polarimetry, the phenomenological reasons for designing a polarimetric sensor, and the primary architectures that have been exploited for developing imaging polarimeters. Considerations on imaging polarimeters such as calibration, optimization, and error performance are also discussed. We review many important sources and examples from the scientific literature.

High-order neural networks have been shown to have impressive computational, storage, and learning capabilities. This performance is because the order or structure of a high-order neural network can be tailored to the order or structure of a problem. Thus, a neural network designed for a particular class of problems becomes specialized but also very efficient in solving those problems. Furthermore, a priori knowledge, such as geometric invariances, can be encoded in high-order networks. Because this knowledge does not have to be learned, these networks are very efficient in solving problems that utilize this knowledge.

CONGESTIVE heart failure has usually been considered to be a global affection of the myocardium in which disturbance of contraction in one or both ventricles is generalized. On the other hand, abnormal myocardial contraction may be caused by local areas of malfunctioning myocardium interacting with other areas of completely normal muscle. The possibility that unco-ordinated contraction of the heart results from such a combination of normal and abnormal muscle has received little attention.In 1925 Wiggers1 described the pattern of left ventricular contraction as a "series of sequential fractionate contractions of muscle bundles." He suggested that disturbance in this temporal . . .

State-dependent Riccati equation (SDRE) techniques are rapidly emerging as general design methods which provide a systematic and effective means of designing nonlinear controllers, observers, and filters. This paper provides an overview of several SDRE design techniques including SDRE nonlinear regulation, SDRE nonlinear H/sub /spl infin//, SDRE nonlinear H/sub 2/, and SDRE nonlinear filtering.

Novel species of microfungi described in the present study include the following from South Africa: Cercosporella dolichandrae from Dolichandra unguiscati, Seiridium podocarpi from Podocarpus latifolius, Pseudocercospora parapseudarthriae from Pseudarthria hookeri, Neodevriesia coryneliae from Corynelia uberata on leaves of Afrocarpus falcatus, Ramichloridium eucleae from Euclea undulata and Stachybotrys aloeticola from Aloe sp. (South Africa), as novel member of the Stachybotriaceae fam. nov. Several species were also described from Zambia, and these include Chaetomella zambiensis on unknown Fabaceae, Schizoparme pseudogranati from Terminalia stuhlmannii, Diaporthe isoberliniae from Isoberlinia angolensis, Peyronellaea combreti from Combretum mossambiciensis, Zasmidium rothmanniae and Phaeococcomyces rothmanniae from Rothmannia engleriana, Diaporthe vangueriae from Vangueria infausta and Diaporthe parapterocarpi from Pterocarpus brenanii. Novel species from the Netherlands include: Stagonospora trichophoricola, Keissleriella trichophoricola and Dinemasporium trichophoricola from Trichophorum cespitosum, Phaeosphaeria poae, Keissleriella poagena, Phaeosphaeria poagena, Parastagonospora poagena and Pyrenochaetopsis poae from Poa sp., Septoriella oudemansii from Phragmites australis and Dendryphion europaeum from Hedera helix (Germany) and Heracleum sphondylium (the Netherlands). Novel species from Australia include: Anungitea eucalyptorum from Eucalyptus leaf litter, Beltraniopsis neolitseae and Acrodontium neolitseae from Neolitsea australiensis, Beltraniella endiandrae from Endiandra introrsa, Phaeophleospora parsoniae from Parsonia straminea, Penicillifer martinii from Cynodon dactylon, Ochroconis macrozamiae from Macrozamia leaf litter, Triposporium cycadicola, Circinotrichum cycadis, Cladosporium cycadicola and Acrocalymma cycadis from Cycas spp. Furthermore, Vermiculariopsiella dichapetali is described from Dichapetalum rhodesicum (Botswana), Ophiognomonia acadiensis from Picea rubens (Canada), Setophoma vernoniae from Vernonia polyanthes and Penicillium restingae from soil (Brazil), Pseudolachnella guaviyunis from Myrcianthes pungens (Uruguay) and Pseudocercospora neriicola from Nerium oleander (Italy). Novelties from Spain include: Dendryphiella eucalyptorum from Eucalyptus globulus, Conioscypha minutispora from dead wood, Diplogelasinospora moalensis and Pseudoneurospora canariensis from soil and Inocybe lanatopurpurea from reforested woodland of Pinus spp. Novelties from France include: Kellermania triseptata from Agave angustifolia, Zetiasplozna acaciae from Acacia melanoxylon, Pyrenochaeta pinicola from Pinus sp. and Pseudonectria rusci from Ruscus aculeatus. New species from China include: Dematiocladium celtidicola from Celtis bungeana, Beltrania pseudorhombica, Chaetopsina beijingensis and Toxicocladosporium pini from Pinus spp. and Setophaeosphaeria badalingensis from Hemerocallis fulva. Novel genera of Ascomycetes include Alfaria from Cyperus esculentus (Spain), Rinaldiella from a contaminated human lesion (Georgia), Hyalocladosporiella from Tectona grandis (Brazil), Pseudoacremonium from Saccharum spontaneum and Melnikomyces from leaf litter (Vietnam), Annellosympodiella from Juniperus procera (Ethiopia), Neoceratosperma from Eucalyptus leaves (Thailand), Ramopenidiella from Cycas calcicola (Australia), Cephalotrichiella from air in the Netherlands, Neocamarosporium from Mesembryanthemum sp. and Acervuloseptoria from Ziziphus mucronata (South Africa) and Setophaeosphaeria from Hemerocallis fulva (China). Several novel combinations are also introduced, namely for Phaeosphaeria setosa as Setophaeosphaeria setosa, Phoma heteroderae as Peyronellaea heteroderae and Phyllosticta maydis as Peyronellaea maydis. Morphological and culture characteristics along with ITS DNA barcodes are provided for all taxa.

This paper presents a gain-scheduled design for a missile longitudinal autopilot. The gain-scheduled design is novel in that it does not involve linearizations about trim conditions of the missile dynamics. Rather, the missile dynamics are brought to a quasilinear parameter varying (LPV) form via a state transformation. An LPV system is defined as a linear system whose dynamics depend on an exogenous variable whose values are unknown a priori but can be measured upon system operation. In this case, the variable is the angle of attack. This is actually an endogenous variable, hence the expression quasi-LPV. Once in a quasi-LPV form, a robust controller using H synthesis is designed to achieve angle-of-attack control via fin deflections. The final design is an inner/outerloop structure, with angle-of-attack control being the inner loop and normal acceleration control being the outer loop.

A computer-controlled Mueller matrix polarimeter with dual rotating retarders is described. Bulk properties of optical materials are determined by controlling the input-polarization state and measuring the output-polarization state. The Mueller matrix of a sample is obtained from polarimetric measurements, and polarization properties, i.e., diattenuation and retardance as well as depolarization, are extracted from the Mueller matrix. Further, fundamental electro- and magneto-optical material properties such as the electro-optical tensor coefficients may be obtained from Mueller matrices measured with applied fields. The polarimeter is currently configured to operate over the 3- to 12-microm spectral region.

A nonlinear control problem has been posed by Bupp et al. to provide a benchmark for evaluating various nonlinear control design techniques. In this paper, the capabilities of the state-dependent Riccati equation (SDRE) technique are illustrated in producing two control designs for the benchmark problem. The SDRE technique represents a systematic way of designing nonlinear regulators. The design procedure consists of first using direct parameterization to bring the nonlinear system to a linear structure having state-dependent coefficients (SDC). A state-dependent Riccati equation is then solved at each point x along the trajectory to obtain a nonlinear feedback controller of the form u=−R-1(x)BT(x)P(x)x, where P(x) is the solution of the SDRE. Analysis of the first design shows that in the absence of disturbances and uncertainties, the SDRE nonlinear feedback solution compares very favorably to the optimal open-loop solution of the posed nonlinear regulator problem, the latter being obtained via numerical optimization. It is also shown via simulation that the closed-loop system has stability robustness against parametric variations and attenuates sinusoidal disturbances. In the second design it is demonstrated how a hard bound can be imposed on the control magnitude to avoid actuator saturation. © 1998 John Wiley & Sons, Ltd.

BACKGROUND: The reliability and measurement error of several impairment measures used during the clinical examination of patients with patellofemoral pain syndrome (PFPS) has not been established. The purpose was to determine the inter-tester reliability and measurement error of measures of impairments associated with PFPS in patients with PFPS. METHODS: A single group repeated measures design was used. Two pairs of physical therapists participated in data collection. Examiners were blinded to each others' measurements. RESULTS: Thirty patients (age 29 +/- 8; 17 female) with PFPS participated in this study. Inter-tester reliability coefficients were substantial for measures of hamstrings, quadriceps, plantarflexors, and ITB/TFL complex length, hip abductors strength, and foot pronation (ICCs from .85 to .97); moderate for measures of Q-angle, tibial torsion, hip external rotation strength, lateral retinacular tightness, and quality of movement during a step down task (ICCs from .67 to .79); and poor for femoral anteversion (ICC of .45). Standard error of measurement (SEM) for measures of muscle length ranged from 1.6 degrees to 4.3 degrees. SEM for Q-angle, tibial torsion, and femoral anteversion were 2.4 degrees, 2.9 degrees, and 4.5 degrees respectively. SEM for foot pronation was 1 mm. SEM for measures of muscle strength was 1.8 Kg for abduction and 2.4 Kg for external rotation. CONCLUSION: Several of the impairments associated with PFPS had sufficient reliability and low measurement error. Further investigation is needed to test if these impairment measurements are related to physical function and whether or not they are useful for decision-making.

Abstract Biologically rich savannas and woodlands dominated by Pinus palustris once dominated the southeastern U.S. landscape. With European settlement, fire suppression, and landscape fragmentation, this ecosystem has been reduced in area by 97%. Half of remnant forests are not burned with sufficient frequency, leading to declines in plant and animal species richness. For these fire‐suppressed ecosystems a major regional conservation goal has been ecological restoration, primarily through the reinitiation of historic fire regimes. Unfortunately, fire reintroduction in long‐unburned Longleaf pine stands can have novel, undesirable effects. We review case studies of Longleaf pine ecosystem restoration, highlighting novel fire behavior, patterns of tree mortality, and unintended outcomes resulting from reintroduction of fire. Many of these pineland restoration efforts have resulted in excessive overstory pine mortality (often >50%) and produced substantial quantities of noxious smoke. The most compelling mechanisms of high tree mortality after reintroduction of fire are related to smoldering combustion of surface layers of organic matter (duff) around the bases of old pines. Development of effective methods to reduce fuels and competing vegetation while encouraging native vegetation is a restoration challenge common to fire‐prone ecosystems worldwide that will require understanding of the responses of altered ecosystems to the resumption of historically natural disturbances.

Oscillatory wing response data were measured on an F-16A aircraft during flutter tests of several external store configurations. Previous testing had shown the F-16 to exhibit limit cycle oscillations (LCO) in the transonic regime, During the present tests, LCO were encountered as well as the sudden onset of high-amplitude oscillations. This sudden high-amplitude response closely resembled that of classical flutter. In all, three distinct categories of response behavior were seen during these tests: classical flutter, typical LCO, and nontypical LCO. These categories are representative of the broad spectrum of aeroelastic responses encountered by fighter aircraft with external stores. Theoretical flutter analyses are shown to adequately identify flutter- or LCO-sensitive store configurations and their instability oscillation frequencies. In addition, a strong correlation between the flight test response and the modal composition of the analytical flutter mechanism is evident. However, the linear analysis fails to provide insight into the oscillation amplitude or onset velocity, which are of primary importance for external store certification on fighter aircraft. Flutter analysis results are presented along with details of the analytical model, the store configurations, and the store mass properties for use as realistic check cases for the validation of nonlinear flutter analysis methods.

The recrystallization of nitroguanidine from N-methyl pyrrolidone and N,N-dimethyl formamide using supercritical fluids and gases near their vapor pressures as anti-solvents was investigated. The nitroguanidine used for the recrystallization study consisted of high aspect ratio needles, 5 x 100 microns; because of its low bulk density the as-produced nitroguanidine is not satisfactorily incorporated into explosives formulations at high solids loading. Depending upon the specific combinations of parameters, the particle size and size distribution could be varied over a wide range, e.g., spherical particles of 100 microns diameter (the desired shape and size), low aspect ratio crystals, unusual star-shaped clusters, loose spherical agglomerates, or monodisperse particles of one micron or less. The results presented for nitroguanidine define a quite general recrystallization concept for processing difficult-to-comminute solids.

An error analysis of a Mueller matrix polarimeter with dual rotating retarders is presented. Errors in orientational alignment of three of the four polarization elements are considered. Errors that are due to nonideal retardation elements are also included in the analysis. Compensation for imperfect retardation elements is possible with the equations derived, and the equations permit a calibration of the polarimeter for azimuthal alignment of polarization elements. An analytical treatment is given and is followed by numerical examples. The latter should prove useful in the laboratory in comparing precalibrated experimental results with theoretical predictions.

BACKGROUND: It is nearly impossible to overestimate the burden of chronic pain, which is associated with enormous personal and socioeconomic costs. Chronic pain is the leading cause of disability in the world, is associated with multiple psychiatric comorbidities, and has been causally linked to the opioid crisis. Access to pain treatment has been called a fundamental human right by numerous organizations. The current COVID-19 pandemic has strained medical resources, creating a dilemma for physicians charged with the responsibility to limit spread of the contagion and to treat the patients they are entrusted to care for. METHODS: To address these issues, an expert panel was convened that included pain management experts from the military, Veterans Health Administration, and academia. Endorsement from stakeholder societies was sought upon completion of the document within a one-week period. RESULTS: In these guidelines, we provide a framework for pain practitioners and institutions to balance the often-conflicting goals of risk mitigation for health care providers, risk mitigation for patients, conservation of resources, and access to pain management services. Specific issues discussed include general and intervention-specific risk mitigation, patient flow issues and staffing plans, telemedicine options, triaging recommendations, strategies to reduce psychological sequelae in health care providers, and resource utilization. CONCLUSIONS: The COVID-19 public health crisis has strained health care systems, creating a conundrum for patients, pain medicine practitioners, hospital leaders, and regulatory officials. Although this document provides a framework for pain management services, systems-wide and individual decisions must take into account clinical considerations, regional health conditions, government and hospital directives, resource availability, and the welfare of health care providers.

Recent advances in wireless technologies have led to several autonomous deployments of such networks. As nodes across distributed networks must co-exist, it is important that all transmitters and receivers are aware of their radio frequency (RF) surroundings so that they can adapt their transmission and reception parameters to best suit their needs. To this end, machine learning techniques have become popular as they can learn, analyze and predict the RF signals and associated parameters that characterize the RF environment. However, in the presence of adversaries, malicious activities such as jamming and spoofing are inevitable, making most machine learning techniques ineffective in such environments. In this paper we propose the Radio Frequency Adversarial Learning (RFAL) framework for building a robust system to identify rogue RF transmitters by designing and implementing a generative adversarial net (GAN). We hope to exploit transmitter specific “signatures” like the in-phase (I) and quadrature (Q) imbalance (i.e., the I/Q imbalance) present in all transmitters for this task, by learning feature representations using a deep neural network that uses the I/Q data from received signals as input. After detection and elimination of the adversarial transmitters RFAL further uses this learned feature embedding as “fingerprints” for categorizing the trusted transmitters. More specifically, we implement a generative model that learns the sample space of the I/Q values of known transmitters and uses the learned representation to generate signals that imitate the transmissions of these transmitters. We program 8 universal software radio peripheral (USRP) software defined radios (SDRs) as trusted transmitters and collect “over-the-air” raw I/Q data from them using a Realtek Software Defined Radio (RTL-SDR), in a laboratory setting. We also implement a discriminator model that discriminates between the trusted transmitters and the counterfeit ones with 99.9% accuracy and is trained in the GAN framework using data from the generator. Finally, after elimination of the adversarial transmitters, the trusted transmitters are classified using a convolutional neural network (CNN), a fully connected deep neural network (DNN) and a recurrent neural network (RNN) to demonstrate building of an end-to-end robust transmitter identification system with RFAL. Experimental results reveal that the CNN, DNN, and RNN are able to correctly distinguish between the 8 trusted transmitters with 81.6%, 94.6% and 97% accuracy respectively. We also show that better “trusted transmission” classification accuracy is achieved for all three types of neural networks when data from two different types of transmitters (different manufacturers) are used rather than when using the same type of transmitter (same manufacturer).

An elevated white blood cell count has many potential etiologies, including malignant and nonmalignant causes. It is important to use age- and pregnancy-specific normal ranges for the white blood cell count. A repeat complete blood count with peripheral smear may provide helpful information, such as types and maturity of white blood cells, uniformity of white blood cells, and toxic granulations. The leukocyte differential may show eosinophilia in parasitic or allergic conditions, or it may reveal lymphocytosis in childhood viral illnesses. Leukocytosis is a common sign of infection, particularly bacterial, and should prompt physicians to identify other signs and symptoms of infection. The peripheral white blood cell count can double within hours after certain stimuli because of the large bone marrow storage and intravascularly marginated pools of neutrophils. Stressors capable of causing an acute leukocytosis include surgery, exercise, trauma, and emotional stress. Other nonmalignant etiologies of leukocytosis include certain medications, asplenia, smoking, obesity, and chronic inflammatory conditions. Symptoms suggestive of a hematologic malignancy include fever, weight loss, bruising, or fatigue. If malignancy cannot be excluded or another more likely cause is not suspected, referral to a hematologist/oncologist is indicated.

The bootstrap filter is an algorithm for implementing recursive Bayesian filters. The required density of the state vector is represented as a set of random samples that are updated and propagated by the algorithm. The method is not restricted by assumptions of linearity or Gaussian noise: It may be applied to any state transition or measurement model. A Monte Carlo simulation example of a bearings-only tracking problem is presented, and the performance of the bootstrap filter is compared with a standard Cartesian extended Kalman filter (EKF), a modified gain EKF, and a hybrid filter. A preliminary investigation of an application of the bootstrap filter to an exoatmospheric engagement with non-Gaussian measurement errors is also given.

This paper develops a theoretical framework for the simple genetic algorithm (combinations of the reproduction, mutation, and crossover operators) based on the asymptotic state behavior of a nonstationary Markov chain algorithm model. The methodology borrows heavily from that of simulated annealing. We prove the existence of a unique asymptotic probability distribution (stationary distribution) for the Markov chain when the mutation probability is used with any constant nonzero probability value. We develop a Cramer's Rule representation of the stationary distribution components for all nonzero mutation probability values and then extend the representation to show that the stationary distribution possesses a zero mutation probability limit. Finally, we present a strong ergodicity bound on the mutation probability sequence that ensures that the nonstationary algorithm (which results from varying mutation probability during algorithm execution) achieves the limit distribution asymptotically. Although the focus of this work is on a nonstationary algorithm in which mutation probability is reduced asymptotically to zero via a schedule (in a fashion analogous to simulated annealing), the stationary distribution results (existence, Cramer's Rule representation, and zero mutation probability limit) are directly applicable to conventional, simple genetic algorithm implementations as well.

The act of creating a new product, system, or process is an innovation; the result of excogitation, study and experimentation. It is an inductive and/or deductive process. The inductive process involves studying systems that exist, for example, in nature, patents and products, and inducing from the behavior of these systems elemental features for innovating novel products. The deductive process involves deducing such aspects from hypothetical concepts and situations where systems or products could exist. By the application of a combined inductive and deductive approach, this paper reports on a methodology for the creation of innovative products with a broader functional repertoire than traditional designs. This breed of innovative products is coined as transformers, transforming into different configurations or according to different states. Current design theory lacks a systematic methodology for the creation of products that have the ability to transform. This paper identifies analogies in nature, patents, and products along with hypothesizing the existence of such products in different environments and situations. Transformation design principles are extracted by studying key design features and functional elements that make up a transforming product. These principles are defined and categorized according to their roles in general transformations. The principles and categorizations are then validated and applied to conceptualize transforming products as part of an innovative design process.

Long-term fire exclusion has altered ecological function in many forested ecosystems in North America. The invasion of fire-sensitive tree species into formerly pyrogenic upland forests in the southeastern United States has resulted in dramatic shifts in surface fuels that have been hypothesized to cause reductions in plant community flammability. The mechanism for the reduced flammability or "mesophication" has lacked empirical study. Here we evaluate a potential mechanism of reduced flammability by quantifying moisture retention (response time and initial moisture capacity) of foliar litter beds from 17 southeastern tree species spanning a wide range of fire tolerance. A k-means cluster analysis resulted in four species groups: a rapidly drying cluster of eight species; a five-species group that absorbed little water but desorbed slowly; a two-species group that absorbed substantial moisture but desorbed rapidly; and a two-species cluster that absorbed substantial moisture and dried slowly. Fire-sensitive species were segregated into the slow moisture loss clusters while fire-tolerant species tended to cluster in the rapid drying groups. Principal-components analysis indicated that several leaf characteristics correlated with absorption capacity and drying rates. Thin-leaved species with high surface area : volume absorbed the greatest moisture content, while those with large, curling leaves had the fastest drying rates. The dramatic shifts in litter fuels as a result of invasion by fire-sensitive species generate a positive feedback that reduce the windows of ignition, thereby facilitating the survival, persistence, and continued invasion of fire-sensitive species in the uplands of the southeastern United States.