Global estimation of range resolved thermodynamic profiles from micropulse differential absorption lidar.

We demonstrate thermodynamic profile estimation with data obtained using the MicroPulse DIAL such that the retrieval is entirely self contained. The only external input is surface meteorological variables obtained from a weather station installed on the instrument. The estimator provides products of temperature, absolute humidity and backscatter ratio such that cross dependencies between the lidar data products and raw observations are accounted for and the final products are self consistent. The method described here is applied to a combined oxygen DIAL, potassium HSRL, water vapor DIAL system operating at two pairs of wavelengths (nominally centered at 770 and 828 nm). We perform regularized maximum likelihood estimation through the Poisson Total Variation technique to suppress noise and improve the range of the observations. A comparison to 119 radiosondes indicates that this new processing method produces improved temperature retrievals, reducing total errors to less than 2 K below 3 km altitude and extending the maximum altitude of temperature retrievals to 5 km with less than 3 K error. The results of this work definitively demonstrates the potential for measuring temperature through the oxygen DIAL technique and furthermore that this can be accomplished with low-power semiconductor-based lidar sensors.

2D signal estimation for sparse distributed target photon counting data.

In this study, we explore the utilization of penalized likelihood estimation for the analysis of sparse photon counting data obtained from distributed target lidar systems. Specifically, we adapt the Poisson Total Variation processing technique to cater to this application. By assuming a Poisson noise model for the photon count observations, our approach yields denoised estimates of backscatter photon flux and related parameters. This facilitates the processing of raw photon counting signals with exceptionally high temporal and range resolutions (demonstrated here to 50 Hz and 75 cm resolutions), including data acquired through time-correlated single photon counting, without significant sacrifice of resolution. Through examination involving both simulated and real-world 2D atmospheric data, our method consistently demonstrates superior accuracy in signal recovery compared to the conventional histogram-based approach commonly employed in distributed target lidar applications.

Mimicking non-ideal instrument behavior for hologram processing using neural style translation.

Holographic cloud probes provide unprecedented information on cloud particle density, size and position. Each laser shot captures particles within a large volume, where images can be computationally refocused to determine particle size and location. However, processing these holograms with standard methods or machine learning (ML) models requires considerable computational resources, time and occasional human intervention. ML models are trained on simulated holograms obtained from the physical model of the probe since real holograms have no absolute truth labels. Using another processing method to produce labels would be subject to errors that the ML model would subsequently inherit. Models perform well on real holograms only when image corruption is performed on the simulated images during training, thereby mimicking non-ideal conditions in the actual probe. Optimizing image corruption requires a cumbersome manual labeling effort. Here we demonstrate the application of the neural style translation approach to the simulated holograms. With a pre-trained convolutional neural network, the simulated holograms are "stylized" to resemble the real ones obtained from the probe, while at the same time preserving the simulated image "content" (e.g. the particle locations and sizes). With an ML model trained to predict particle locations and shapes on the stylized data sets, we observed comparable performance on both simulated and real holograms, obviating the need to perform manual labeling. The described approach is not specific to holograms and could be applied in other domains for capturing noise and imperfections in observational instruments to make simulated data more like real world observations.

Optimization of linear signal processing in photon counting lidar using Poisson thinning.

Photon counting lidar signals generally require smoothing to suppress random noise. While the process of reducing the resolution of the profile reduces random errors, it can also create systematic errors due to the smearing of high gradient signals. The balance between random and systematic errors is generally scene dependent and difficult to find, because errors caused by blurring are generally not analytically quantified. In this work, we introduce the use of Poisson thinning, which allows optimal selection of filter parameters for a particular scene based on quantitative evaluation criteria. Implementation of the optimization step is relatively simple and computationally inexpensive for most photon counting lidar processing.

Key diagnostic markers for autoimmune lymphoproliferative syndrome with molecular genetic diagnosis.

Autoimmune lymphoproliferative syndrome (ALPS) is a rare immunodeficiency caused by mutations in genes affecting the extrinsic apoptotic pathway (FAS, FASL, CASP10). This study evaluated the clinical manifestations, laboratory findings, and molecular genetic results of 215 patients referred as possibly having ALPS. Double-negative T-cell (DNT) percentage and in vitro apoptosis functional tests were evaluated by fluorescence-activated cell sorting; interleukin 10 (IL-10) and IL-18 and soluble FAS ligand (sFASL) were measured by enzyme-linked immunosorbent assay. Genetic analysis was performed by next-generation sequencing. Clinical background data were collected from patients' records. Patients were categorized into definite, suspected, or unlikely ALPS groups, and laboratory parameters were compared among these groups. Of 215 patients, 38 met the criteria for definite ALPS and 17 for suspected ALPS. The definite and suspected ALPS patient populations showed higher DNT percentages than unlikely ALPS and had higher rates of lymphoproliferation. Definite ALPS patients had a significantly more abnormal in vitro apoptosis function, with lower annexin, than patients with suspected ALPS (P = .002) and patients not meeting ALPS criteria (P < .001). The combination of elevated DNTs and an abnormal in vitro apoptosis functional test was the most useful in identifying all types of ALPS patients; the combination of an abnormal in vitro apoptosis functional test and elevated sFASLs was a predictive marker for ALPS-FAS group identification. Lymphoproliferation, apoptosis functional test, and DNTs are the most sensitive markers; elevated IL-10 and IL-18 are additional indicators for ALPS. The combination of elevated sFASLs and abnormal apoptosis function was the most valuable prognosticator for patients with FAS mutations.

Demonstration of a combined differential absorption and high spectral resolution lidar for profiling atmospheric temperature.

This work presents the first demonstration of atmospheric temperature measurement using the differential absorption lidar (DIAL) technique. While DIAL is routinely used to measure atmospheric gases such as ozone and water vapor, almost no success has been found in using DIAL to measure atmospheric temperature. Attempts to measure temperature using a well-mixed gas like oxygen (O2) have largely failed based on a need for quantitative ancillary measurements of water vapor and atmospheric aerosols. Here, a lidar is described and demonstrated that simultaneously measures O2 absorption, water vapor number density, and aerosol backscatter ratio. This combination of measurements allows for the first measurements of atmospheric temperature with useful accuracy. DIAL temperature measurements are presented to an altitude of 4 km with 225 m and 30 min resolution with accuracy better than 3 K. DIAL temperature data is compared to a co-located Raman lidar system and radiosondes to evaluate the system's performance. Finally, an analysis of current performance characteristics is presented, which highlights pathways for future improvement of this proof-of-concept instrument.

Modeling the performance of a diode laser-based (DLB) micro-pulse differential absorption lidar (MPD) for temperature profiling in the lower troposphere.

Ground-based, network-deployable remote sensing instruments for thermodynamic profiling in the lower troposphere are needed by the atmospheric science research community. The recent development of a low-cost diode-laser-based (DLB) micro-pulse differential absorption lidar (DIAL) has begun to address the need for ground-based remote sensing instruments for water vapor profiling in the lower troposphere. Now, taking advantage of the broad spectral coverage of the DLB architecture, an enhancement to the water vapor micro-pulse DIAL (MPD) instrument is proposed to enable atmospheric temperature profiling. The new instrument is based on measuring a temperature-dependent oxygen (O2) absorption coefficient and using this to retrieve the range-resolved temperature profile. In this paper, a retrieval method is proposed based on the recently developed perturbative solution to the DIAL equation that takes into account the Doppler broadening of the molecularly backscattered signal. This perturbative solution relies on an ancillary high spectral resolution lidar (HSRL) measurement of the backscatter ratio. Data from an operational water vapor MPD combined with a DLB-HSRL were used to create an atmosphere model, from which return signals for the O2-MPD were generated. The perturbative retrieval was then applied to these data and a comparison of the retrieved temperature and the model temperature profile allowed the efficacy of retrieval to be evaluated. The results indicate that the temperature profile may be retrieved from a theoretical O2-MPD instrument with a ±1 K accuracy up to 2.5 km and ±3 K accuracy up to 4.5 km with a 150 m range resolution and 30-minute averaging time. Using data from a recently developed O2-MPD in combination with a WV-MPD, and a DLB-HSRL, an initial temperature retrieval is demonstrated. The results of this initial demonstration are consistent with the performance modeling.

Fast computation of absorption spectra for lidar data processing using principal component analysis.

We describe a principal component-based technique for approximating absorption and scattering spectra commonly needed for lidar signal processing. Where previously these calculations had been bottlenecks in our lidar signal processing, the described approach has increased our spectrum calculation speed by over two orders of magnitude. The described approach also allows analytically calculated temperature and pressure derivatives, which is useful for propagating uncertainty and implementation of global optimization algorithms.

Nonlinear target count rate estimation in single-photon lidar due to first photon bias.

The use of time-tagging single-photon lidar for high-resolution ranging and backscattered count rate measurements requires special attention to mitigate biases and distortions typically not seen in full-waveform lidar sensors. Specifically, sub-pulse sampling and the presence of non-zero receiver dead-time generates an effect named first photon bias (FPB). FPB manifests itself as an intensity-induced ranging offset, previously documented, and a nonlinear count rate with integrated distribution distortions. These combined effects require special attention when integrating lidar point clouds to accurately estimate the backscattered signal strength and true range. This Letter indicates that correcting solely for the introduced range bias does not address the nonlinear shape distortions in the accumulated photon distribution. Analyses of distribution widths and estimated signal strengths must consider both effects. We present an analysis that demonstrates the cause and effect of the FPB on photon time-tagging integrated photon distributions using the Monte Carlo method, relates the modeled results to previously published data and statistics, and provides a framework for interpreting range and backscattered signal strength measurements from these sensors.

Perturbative solution to the two-component atmosphere DIAL equation for improving the accuracy of the retrieved absorption coefficient.

Thermodynamic profiling using ground-based remote sensing instruments such as differential absorption lidar (DIAL) has the potential to fill observational needs for climate and weather-related research and improve weather forecasting. The DIAL technique uses the return signal resulting from atmospherically scattered light at two closely spaced wavelengths to determine the range-resolved absorption coefficient for a molecule of interest. Temperature profiles can be retrieved using a temperature-sensitive absorption feature of a molecule with a known mixing ratio such as oxygen. In order to obtain accuracies of less than 1 K, the narrowband DIAL equation must be expanded to account for Doppler broadening of molecular backscatter, and its relative contribution to the total signal, the backscatter ratio, must be known. While newly developed low-cost high spectral resolution lidar (HSRL) can measure backscatter ratio with sufficient accuracy, the frequency-resolved DIAL equation, even with this information, remains transcendental, and solving it for temperature can be computationally expensive. In this paper, we present a perturbative solution to the frequency-resolved DIAL equation when we have an HSRL providing the required ancillary measurements. This technique leverages perturbative techniques commonly employed in quantum mechanics and has the ability to obtain accurate temperature profiles (better than 1 K) with low computational cost. The perturbative solution is applied to a modeled atmosphere as an initial demonstration of this retrieval technique. An initial estimate of the error in the temperature retrieval for a diode-laser-based O2 DIAL is presented, indicating that temperature retrievals with an error of less than ±1 K can be achieved in the lower troposphere. While this paper focuses on temperature measurements, the perturbative solution to the DIAL equation can also be used to improve the accuracy of retrieved number density profiles.

Demonstration of a diode-laser-based high spectral resolution lidar (HSRL) for quantitative profiling of clouds and aerosols.

We present a demonstration of a diode-laser-based high spectral resolution lidar. It is capable of performing calibrated retrievals of aerosol and cloud optical properties at a 150 m range resolution with less than 1 minute integration time over an approximate range of 12 km during day and night. This instrument operates at 780 nm, a wavelength that is well established for reliable semiconductor lasers and detectors, and was chosen because it corresponds to the D2 rubidium absorption line. A heated vapor reference cell of isotopic rubidium 87 is used as an effective and reliable aerosol signal blocking filter in the instrument. In principle, the diode-laser-based high spectral resolution lidar can be made cost competitive with elastic backscatter lidar systems, yet delivers a significant improvement in data quality through direct retrieval of quantitative optical properties of clouds and aerosols.

Development of an ELISA-Based Competitive Binding Assay for the Analysis of Drug Concentration and Antidrug Antibody Levels in Patients Receiving Adalimumab or Infliximab.

BACKGROUND: There is increasing interest in measuring both drug and antidrug antibody (ADA) levels in patients receiving anti-tumor necrosis factor treatment as part of algorithms for guiding therapeutic strategies. Many of the current assays for ADA detection have limitations with respect to specificity, sensitivity, and/or laboratory requirements. Specific identification of ADA based on their inhibitory activity in a simple competitive binding assay remains problematic. The development of an enzyme-linked immunosorbent assay (ELISA)-based method for detection of both drug and ADA in patients receiving either adalimumab or infliximab would widen availability of monitoring for these patients. METHODS: An ELISA for the specific detection of adalimumab and infliximab using widely available reagents was developed. A simple modification for the detection of ADA capable of competitively inhibiting the in vitro binding of drug to solid phase tumor necrosis factor was also developed. Drug and ADA levels were analyzed in patients with rheumatoid arthritis and inflammatory bowel disease. RESULTS: The ELISA specifically detected drug concentrations in patient sera with no evidence of positive or negative interference by rheumatoid factor positive control sera. A subset of those patients with low drug concentrations had detectable levels of ADA with inhibitory activity in a competitive binding assay. Spiking with both drugs confirmed the specificity of the ADA detected. CONCLUSIONS: A modified ELISA protocol can be used to for the detection of both drug concentrations and ADA in patients receiving either adalimumab or infliximab. The ELISA incorporates those features identified in the literature as important for the accurate analysis of these antibodies and uses laboratory facilities and reagents that are widely available. It therefore provides a relatively simple and low cost assay for therapeutic drug monitoring of inpatients receiving adalimumab or infliximab.

Polarization lidar observations of backscatter phase matrices from oriented ice crystals and rain.

Oriented particles can exhibit different polarization properties than randomly oriented particles. These properties cannot be resolved by conventional polarization lidar systems and are capable of corrupting the interpretation of depolarization ratio measurements. Additionally, the typical characteristics of backscatter phase matrices from atmospheric oriented particles are not well established. The National Center for Atmospheric Research High Spectral Resolution Lidar was outfitted in spring of 2012 to measure the backscatter phase matrix, allowing it to fully characterize the polarization properties of oriented particles. The lidar data analyzed here considers operation at 4°, 22° and 32° off zenith in Boulder, CO, USA (40.0°N,105.2°W). The HSRL has primarily observed oriented ice crystal signatures at lidar tilt angles near 32° off zenith which corresponds to an expected peak in backscatter from horizontally oriented plates. The maximum occurrence frequency of oriented ice crystals is measured at 5 km, where 2% of clouds produced significant oriented ice signatures by exhibiting diattenuation in their scattering matrices. The HSRL also observed oriented particle characteristics of rain at all three tilt angles. Oriented signatures in rain are common at all three tilt angles. As many as 70% of all rain observations made at 22° off zenith exhibited oriented signatures. The oriented rain signatures exhibit significant linear diattenuation and retardance.

Management of medication in patients with Parkinson's disease who are nil-by-mouth.

Parkinson's disease affects approximately 200 in every 100000 patients in London (Schrag et al, 2000). These individuals experience increased rates of emergency admissions to hospital secondary to falls, fractures, impaired mobility, infections, psychiatric disturbances and cardiovascular disease. The duration of their hospital stay is frequently prolonged compared to patients who do not have Parkinson's disease (Woodford and Walker, 2005). In addition, significant numbers of patients with Parkinson's disease are admitted for elective surgery.

Professional killer cell deficiencies and decreased survival in pulmonary arterial hypertension.

BACKGROUND AND OBJECTIVE: Increasing evidence implicates lymphocytes in pulmonary arterial hypertension (PAH) pathogenesis. Rats deficient in T-lymphocytes show increased propensity to develop PAH but when injected with endothelial progenitor cells are protected from PAH (a mechanism dependent on natural killer (NK) cells). A decreased quantity of circulating cytotoxic CD8+ T-lymphocytes and NK cells are now reported in PAH patients; however, the effect of lymphocyte depletion on disease outcome is unknown. METHODS: This prospective study analysed the lymphocyte profile and plasma brain natriuretic peptide (BNP) levels of patients with idiopathic PAH (IPAH), connective tissue disease-associated PAH (CTD-APAH) and matched healthy controls. Lymphocyte surface markers studied include: CD4+ (helper T-cell marker), CD8+ (cytotoxic T-cell marker), CD56/CD16 (NK cell marker) and CD19+ (mature B-cell marker). Lymphocyte deficiencies and plasma BNP levels were then correlated with clinical outcome. RESULTS: Fourteen patients with PAH (9 IPAH, 5CTD) were recruited. Three patients were deceased at 1-year follow-up; all had elevated CD4 : CD8 ratios and deficiencies of NK cells and cytotoxic CD8+ T-lymphocytes at recruitment. Patients with normal lymphocyte profiles at recruitment were all alive a year later, and none were on the active transplant list. As univariate markers, cytotoxic CD8+ T-cell and NK cell counts were linked to short-term survival. CONCLUSIONS: Deficiencies in NK cells and cytotoxic CD8+ T-cells may be associated with an increased risk of death in PAH patients. Further research is required in larger numbers of patients and to elucidate the mechanism of these findings.

General description of polarization in lidar using Stokes vectors and polar decomposition of Mueller matrices.

Polarization measurements have become nearly indispensible in lidar cloud and aerosol studies. Despite polarization's widespread use in lidar, its theoretical description has been widely varying in accuracy and completeness. Incomplete polarization lidar descriptions invariably result in poor accountability for scatterer properties and instrument effects, reducing data accuracy and disallowing the intercomparison of polarization lidar data between different systems. We introduce here the Stokes vector lidar equation, which is a full description of polarization in lidar from laser output to detector. We then interpret this theoretical description in the context of forward polar decomposition of Mueller matrices where distinct polarization attributes of diattenuation, retardance, and depolarization are elucidated. This decomposition can be applied to scattering matrices, where volumes consisting of randomly oriented particles are strictly depolarizing, while oriented ice crystals can be diattenuating, retarding, and depolarizing. For instrument effects we provide a description of how different polarization attributes will impact lidar measurements. This includes coupling effects due to retarding and depolarization attributes of the receiver, which have no description in scalar representations of polarization lidar. We also describe how the effects of polarizance in the receiver can result in nonorthogonal polarization detection channels. This violates one of the most common assumptions in polarization lidar operation.

Polarization lidar operation for measuring backscatter phase matrices of oriented scatterers.

We describe implementation and demonstration of a polarization technique adapted for lidar to measure all unique elements of the volume backscatter phase matrix. This capability allows for detection of preferential orientation within a scattering volume, and may improve scattering inversions on oriented ice crystals. The technique is enabled using a Mueller formalism commonly employed in polarimetry, which does not require the lidar instrument be polarization preserving. Instead, the accuracy of the polarization measurements are limited by the accuracy of the instrument characterization. A high spectral resolution lidar at the National Center for Atmospheric Research was modified to demonstrate this polarization technique. Two observations where the instrument is tilted off zenith are presented. In the first case, the lidar detects flattened large raindrops oriented along the same direction due to drag forces from falling. The second case is an ice cloud approximately 5 km above lidar base that contains preferentially oriented ice crystals in a narrow altitude band.

Polarization lidar for shallow water depth measurement.

A bathymetric, polarization lidar system transmitting at 532 nm and using a single photomultiplier tube is employed for applications of shallow water depth measurement. The technique exploits polarization attributes of the probed water body to isolate surface and floor returns, enabling constant fraction detection schemes to determine depth. The minimum resolvable water depth is no longer dictated by the system's laser or detector pulse width and can achieve better than 1 order of magnitude improvement over current water depth determination techniques. In laboratory tests, an Nd:YAG microchip laser coupled with polarization optics, a photomultiplier tube, a constant fraction discriminator, and a time-to-digital converter are used to target various water depths with an ice floor to simulate a glacial meltpond. Measurement of 1 cm water depths with an uncertainty of ±3 mm are demonstrated using the technique. This novel approach enables new approaches to designing laser bathymetry systems for shallow depth determination from remote platforms while not compromising deep water depth measurement.