Signal Saturation Research Articles

Optimizing the size of cylindrical sucrose solid state/EPR dosimeters for ionizing radiation

This work continuous our previous investigation regards the saturation of dose response of irradiated sucrose Solid State/Electron Paramagnetic Resonance (SS/EPR) dosimeters at doses higher than 10 kGy. Cylindrical sucrose dosimeters with different sizes (diameter and height) have been studied. The main purpose of the current study is by optimizing of the dosimeter size to avoid saturation of the EPR signal at high doses. In view of this it has been researched dosimeters with diameters 2, 3 and 4 mm and heights 5, 10 and 14 mm. From the obtained results have been found that with decreased of the diameter of the dosimeters from 4 to 2 mm the intensity of the EPR signal became linearly depended from the absorbed dose radiation in the dose range 1–50 kGy. In the dosimeters with diameters 3 and 4 mm a weak saturation of the dose response curves at higher doses have been observed. This confirms our previous claim that the saturation is due to simultaneously impact of the deeper penetration of the samples in the electric field in the EPR cavity and of the irradiation with high dose gamma rays. The increased of the height of the dosimeters from 5 to 14 mm aims to increase the sensitivity and to some extent to compensate the loss of sensitivity due to the smaller diameter. Charcoal samples with the same shape have been used for comparison.

Fast-ion Dα spectroscopy diagnostic at KSTAR.

A fast-ion Dα (FIDA) diagnostics system was installed for core and edge measurements on KSTAR. This system has two tangential FIDA arrays that cover both blue- and redshifted Dα lines (cold: 656.09nm) in active views along the neutral beam 1A centerline. The spectral band is 647-662.5nm, and it covers the Doppler shift of the emission from the maximum energy of the neutral beam (100 keV). A curved filter strip with a motorized stage adequately prevents saturation of the electron multiplying charge-coupled device signal by the cold Dα line from the plasma edge. From comparisons of the measured spectra and FIDASIM modeling code, the FIDA spectra are well matched quantitatively. Moreover, the first measurements show that the FIDA radiance agrees with the neutron rate in the time trace during external heating and perturbation. In addition, responses are observed in the core FIDA radiance during the edge-localized mode cycle.

Picosecond two-photon absorption laser-induced fluorescence (ps-TALIF) in krypton: The role of photoionization on the density depletion of the fluorescing state Kr 5p′[3/2

The present study focuses on the application of a picosecond (ps) two-photon absorption laser-induced fluorescence (TALIF) technique in krypton (Kr) at variable pressure (0.1–10 mbar). The laser intensity (I, units W cm−2) is tuned between 1 and 480 MW cm−2, and the depletion of the density of the Kr 5p′[3/2]2 fluorescing state through photoionization (PIN) and amplified stimulated emission (ASE) is investigated. This is done by combining TALIF experiments with a simple 0D numerical model. We demonstrate that for a gas pressure of 3 mbar and 15 <I≤ 480 MW cm−2, a saturated fluorescence signal is obtained, which is largely attributed to PIN, ASE being negligible. Also, a broadening of the two-photon absorption line (i.e., 4p6 1S0 →→ 5p′[3/2]2) is recorded due to the production of charged species through PIN, inducing a Stark effect. For I ≤ 15 MW cm−2, though, PIN is significantly limited, the absorption line is noticeably narrowed, and the quadratic dependence of the TALIF signal intensity vs the laser energy is obtained. Thus, in this case, the investigated Kr TALIF scheme, using the 5p′[3/2]2 → 5s[3/2]1 fluorescence channel, can be used for calibration purposes in ps-TALIF experiments. These results are of interest for fundamental research since most ps-TALIF studies performed in Kr do not investigate in detail the role of PIN and ASE on the depletion of the Kr 5p′[3/2]2 state density. Moreover, this work contributes to the development of ps-TALIF for determining absolute densities and quenching coefficients of H and N atoms in plasmas. The use of ps-TALIF can allow sub-ns measurements of quenching rates that are necessary for absolute atomic densities determination in atmospheric pressure plasmas. Thus, the present study is linked to many experimental works focused on plasma physics and applications. In fact, the investigation of the application of ps-TALIF in Kr and the definition of regimes where the TALIF signal intensity scales quadratically with the laser energy is essential to calibrate H and N atom densities in reactive plasmas.

Improved estimation of forest stand volume by the integration of GEDI LiDAR data and multi-sensor imagery in the Changbai Mountains Mixed forests Ecoregion (CMMFE), northeast China

Forest stand volume is a vital indicator of productivity and carbon storage. Conventionally, stand volume is estimated from field samples, Synthetic Aperture Radar (SAR), and optical imagery, which suffer saturation problems. Although Light Detection and Ranging (LiDAR) technique degrades the signal saturation, its large-scale application is hindered by spatial continuity. To address this issue, recently released Global Ecosystem Dynamics Investigation (GEDI) LiDAR data, Sentinel-1 SAR, Sentinel-2 Multispectral Instrument (MSI), and Advanced Land Observing Satellite (ALOS) digital surface model (DSM) imagery were integrated for volume modeling and estimation under a point-line-polygon framework. The footprint-level LiDAR variables, as a linear bridge, were adopted to link field plots to the full-cover multi-sensor imagery. Results showed that volume of the Changbai Mountains Mixed Forests Ecoregion (CMMFE) displayed variations along the elevation gradient, ranging from 47.56 to 277.30 m3/ha with a mean value of 151.39 m3/ha. Additionally, the accuracy comparison based on independent validation samples indicated that integrating GEDI LiDAR data under a point-line-polygon framework performed better than the traditional point-polygon approach, which directly linked field samples to multi-sensor imagery. The corresponding estimated error declined from 22.08% to 15.21%. The canopy cover and tree height from LiDAR, elevation from L band InSAR, and spectral indices of MSI red-edge bands were key for stand volume mapping in heterogeneous temperate forests. This comparison also showed that the integration of LiDAR by a point-line-polygon framework adopted 2/3 of the modeling points but acquired more accurate estimation than a traditional approach only based on multi-sensor imagery, which implied less field sampling work was needed for similar research. Consequently, as a pioneering exploration of GEDI LiDAR data combined with multi-sensor imagery under the point-line-polygon framework, this study provides an efficient methodology for the volume estimation of heterogeneous forests.

Estimation of tree height and aboveground biomass of coniferous forests in North China using stereo ZY-3, multispectral Sentinel-2, and DEM data

The forest tree height and aboveground biomass (AGB) are important indicators for monitoring changes and trends in forest carbon storage and terrestrial carbon fluxes. Accurate large-scale wall-to-wall mapping of the forest tree height and AGB remain challenging due to the limited data availability for extraction tree height and the data signal saturation problem in AGB estimation. In this study, we explored the potential of forest tree height mapping using stereo imageries, and analyzed whether accounting for such information, in addition to optical sensor data, could improve the performance of AGB estimations of coniferous forests in a case study in North China. First, a spatially continuous tree height product was obtained using Ziyuan-3 satellite (ZY-3) stereo images combined with a digital elevation model (DEM) obtained from Advanced Land Observing Satellite (ALOS) data. Second, two AGB estimation models were established by combining the forest tree height with vegetation index, spectral, biophysical (from Sentinel-2 images), and topographic variables. A random forest algorithm was utilized to evaluate the effect of including the tree height variable in the AGB estimation. The results showed that the tree height estimation using the nadir and forward views of the ZY-3 stereo images was more accurate than that based on the nadir and backward views from the same images. The AGB estimation model incorporating the tree height variable with a coefficient of determination value of 0.7789, a root mean square error (RMSE) value of 29.815 Mg/ha and a relative RMSE of 23.42% was more robust and effective, thereby demonstrating thatthe tree height variable can be used to alleviate the data signal saturation issue successfully. The proposed approach can provide new insight into forest tree height mapping and AGB products obtained from satellite stereo images and freely accessible Sentinel-2 multispectral images.

Predictive Performance Comparison of Computed Linear and Quadratic Multivariate Models for In-Situ UV Fiber Optics Tablet Dissolution Testing

A present investigation aimed for multivariate modeling as a solution to resolve inaccuracy in dissolution testing experienced in the use of in-situ UV fiber optics dissolution systems (FODS) due to signal saturation problems. This problem is specifically encountered with high absorbance of moderate to high dose formulations. A high absorbance not only impede a real-time assessment but can also result in inaccurate dissolution profiles. Full spectra (F) and low absorbance regions (L) were employed to develop linear and quadratic (Q) partial least squares (PLS) and principal component regression (PCR) models. The conventional dissolution of atenolol, ibuprofen, and metformin HCl immediate-release (IR) tablets followed by HPLC analysis was used as a reference method to gauge multivariate models' performance in the 'built-in' Opt-Diss model. The linear multivariate modeling outputs resulted in accurate dissolution profiles, despite the potentially high UV signal saturation at later time points. Conversely, the 'built-in' Opt-Diss model and multivariate quadratic models failed to predict dissolution profiles accurately. The current studies show a good agreement in the predictions across both low absorbance region and full spectra, demonstrating the multivariate models' robust predictability. Overall, linear PLS and PCR models showed statistically similar results, which demonstrated their applicative flexibility for using FODS despite signal saturation and provides a unique alternative to traditional and labor-intensive UV or HPLC dissolution testing.

Saturated signals in spectroscopic imaging: why and how should we deal with this regularly observed phenomenon?

We have all been confronted one day by saturated signals observed on acquired spectra, whatever the technique considered. A saturation, also known as clipping in signal processing, is a form of distortion that limits a signal once it exceeds a threshold. As a consequence, clipped or saturated bands with their characteristic plateau present numerical values that do not correspond to the analytical reality of the analyzed sample. Of course, analysts know that they cannot consider these erroneous values and therefore reconsider either sample preparation or instrument settings. Unfortunately, there are many experiments today (and this is the case in spectroscopic imaging) for which we will not be able to fight against the saturation effect that will undeniably be observed on the acquired spectra. The aim of this article is first to show why it is important to correct these saturation effects at the risk of having a biased view of the sample and more specifically in the context of multivariate data analysis. In a second step, we will look at strategies for managing saturated bands. An original concept will then be presented by considering saturated values as missing ones. A statistical imputation strategy will then be implemented in order to recover the information lost during the measurement.

Development of a narrow stopband filter for spectroscopic fast ion deuterium-alpha measurements.

A new technique to attenuate the unshifted deuterium Balmer-alpha (D-alpha) emission is developed and tested for the fast ion D-alpha (FIDA) diagnostic. The unshifted D-alpha emission, at λ = 656.1nm, is around three orders of magnitude higher than the desired FIDA emission. Blocking the strong emission feature is essential to prevent blooming and light smearing on the CCD chip and scattered light contamination. The new method is a notch filter approach that utilizes the reflection from ultra-narrow bandpass filters to block the saturating signal before it enters the spectrometer. Collimated light from the fibers is reflected off the filter at a 15° angle of incidence. Measurements show that a center wavelength transmission of 0.006 and a blocking full width at half maximum of ∼1 nm are achieved by using a 200 μm fiber and a 20mm focal length collimator with two filters.

Infrared radiofluorescence (IR-RF) dating: A review

Luminescence dating methods on natural minerals such as quartz and feldspars are indispensable for establishing chronologies in Quaternary Science. Commonly applied sediment dating methods are optically stimulated luminescence (OSL) and infrared stimulated luminescence (IRSL). In 1999, Trautmann et al. (1999a, b) proposed a new related technique called infrared radiofluorescence (IR-RF). IR-RF denotes the infrared luminescence signal of feldspar resulting from exposure to ionizing radiation and potentially offers a significant methodological advance compared to OSL and IRSL regarding luminescence signal stability, dating range and required measurement time. The method has rarely been applied due to a lack of commercially available measurement equipment but experienced a revival during the last years. The present article provides a state-of-the-art overview of the physical background of IR-RF, its challenges, applications and the potential as a dating method. The paper particularly addresses practical considerations for applying IR-RF dating, including signal bleachability and saturation behaviour, and summarizes proposed solutions.

Machine learning-assisted calibration of Hg2+ sensors based on carbon nanotube field-effect transistors

Nanomaterial-based electronic sensors have demonstrated ultra-low detection limits, down to parts-per-billion (ppb) or parts-per-trillion (ppt) concentrations. However, these extreme sensitivities also make them susceptible to signal saturation at higher concentrations and restrict their usage primarily to low concentrations. Here, we report machine learning techniques to create a calibration method for carbon nanotube-based field-effect transistor (FET) devices. We started with linear regression, followed by regression splines to capture the non-linearity in the data. Further improvements in model performance were obtained with regression trees. Finally we lowered the model variance and further boosted the model performance by introducing random forest. The resulting performance as measured by R2 was estimated to be 0.8260 using out-of-bag error. The methodology avoids saturation and extends the dynamic range of the nanosensors up to 12 orders of magnitude in analyte concentrations. Further investigations of the sensing mechanism include analysis of feature importance in each of the model we tested. Functionalized nanosensors demonstrate selective detection of Hg2+ ions with detection limits 10−14.36±0.78 M, and maintain calibration to concentrations as high as 1 mM. Application of machine learning techniques to investigate which features in the FET signal maximally correlate with concentration changes provide valuable insight into the carbon nanotube sensing mechanism and assist in the rational design of future nanosensors.

Cu2-xO-functionalized plastic optical fiber for H2S sensing

A Plastic Optical Fiber (POF) in U-shape, functionalized with a thin film of copper oxide, was developed as a hydrogen sulfide gas sensor. Unlike resistive-type Semiconductor Metal Oxide (SMOX) gas sensors, the present optical sensing probe is neither electrically charged nor demands a heating system as it functions at room temperature (25 °C). Pulsed Laser Deposition (PLD) method was used to coat optical fibers with copper, nickel and tin oxides. However, only CuO-functionalized fibers demonstrated a detectable signal to the H2S exposure. The PLD copper oxide thin films were composed of a dominantly amorphous structure and embedded Cu2-xO crystallites. Fourier Transform Infrared Spectroscopy (FTIR) demonstrated that the PLD process created negatively charged oxygen species adsorbed on the surface of the Cu2-xO, which react with H2S are responsible for the sensing mechanism. A state-of-the-art modification in the fiber’s geometry, with more curves, was presented and improved the Signal to Noise Ratio (SNR). The sensor demonstrated a response time as low as 1 min during an exposure to 200 ppm H2S and a minimum detectable H2S concentration, CH2S, around 10 ppm. The experimental data led to an interpolation that estimates a logarithmic relationship between the saturated signal and CH2S. The sensor demonstrates a remarkable selectivity to H2S. Furthermore, the saturated signal represents an inverse relation with the Relative Humidity (RH).

Probing the myelin water compartment with a saturation-recovery, multi-echo gradient-recalled echo sequence.

To investigate the effect of varying levels of -weighting on the evolution of the complex signal from white matter in a multi-echo gradient-recalled echo (mGRE) saturation-recovery sequence. Analysis of the complex signal evolution in an mGRE sequence allows the contributions from short- and long- components to be separated, thus providing a measure of the relative strength of signals from the myelin water, and the external and intra-axonal compartments. Here we evaluated the effect of different levels of -weighting on these signals, expecting that the previously reported, short of the myelin water would lead to a relative enhancement of the myelin water signal in the presence of signal saturation. Complex, saturation-recovery mGRE data from the splenium of the corpus callosum from 5 healthy volunteers were preprocessed using a frequency difference mapping (FDM) approach and analyzed using the 3-pool model of complex signal evolution in white matter. An increase in the apparent as a function of echo time was demonstrated, but this increase was an order of magnitude smaller than that expected from previously reported myelin water -values. This suggests the presence of magnetization transfer and exchange effects which counteract the -weighting. Variation of the amplitude in a saturation-recovery mGRE sequence can be used to modulate the relative strength of signals from the different compartments in white matter, but the modulation is less than predicted from previously reported -values.

Doubly Photopolymerized Holographic Sensors.

Holographic sensors are two-dimensional (2D) photonic crystals that diffract narrow-band light in the visible spectrum to quantify analytes in aqueous solutions. Here, a holographic fabrication setup was developed to produce holographic sensors through a doubly polymerization system of a poly-2-hydroxyethyl methacrylate hydrogel film using a pulsed Nd:YAG laser (λ = 355 nm, 5 ns, 100 mJ). Wavelength shifts of holographic Bragg peak in response to alcohol species (0-100 vol %) were characterized. Diffraction spectra showed that the holographic sensors could be used for short-chain alcohols at concentrations up to 60 vol %. The reversibility of the sensor was demonstrated, exhibiting a response time of 7.5 min for signal saturation. After 30 cycles, the Bragg peak and color remained the same in both 20 and 60 vol %. The fabrication parameters were simulated in MATLAB using a 2D finite-difference time-domain algorithm to model the interference pattern and energy flux profile of laser beam recording in the hydrogel medium. This work demonstrates a particle-free holographic sensor that offers continuous, reversible, and rapid colorimetric readouts for the real-time quantification of alcohols.

A Convolutional Neural Network Architecture to Enhance Oximetry Ability to Diagnose Pediatric Obstructive Sleep Apnea.

This study aims at assessing the usefulness of deep learning to enhance the diagnostic ability of oximetry in the context of automated detection of pediatric obstructive sleep apnea (OSA). A total of 3196 blood oxygen saturation (SpO2) signals from children were used for this purpose. A convolutional neural network (CNN) architecture was trained using 20-min SpO2 segments from the training set (859 subjects) to estimate the number of apneic events. CNN hyperparameters were tuned using Bayesian optimization in the validation set (1402 subjects). This model was applied to three test sets composed of 312, 392, and 231 subjects from three independent databases, in which the apnea-hypopnea index (AHI) estimated for each subject (AHICNN) was obtained by aggregating the output of the CNN for each 20-min SpO2 segment. AHICNN outperformed the 3% oxygen desaturation index (ODI3), a clinical approach, as well as the AHI estimated by a conventional feature-engineering approach based on multi-layer perceptron (AHIMLP). Specifically, AHICNN reached higher four-class Cohen's kappa in the three test databases than ODI3 (0.515 vs 0.417, 0.422 vs 0.372, and 0.423 vs 0.369) and AHIMLP (0.515 vs 0.377, 0.422 vs 0.381, and 0.423 vs 0.306). In addition, our proposal outperformed state-of-the-art studies, particularly for the AHI severity cutoffs of 5 e/h and 10 e/h. This suggests that the information automatically learned from the SpO2 signal by deep-learning techniques helps to enhance the diagnostic ability of oximetry in the context of pediatric OSA.

Effect of the restoration of saturated signals in hyperspectral image analysis and color reproduction

In hyperspectral imaging, the captured signal is often affected by saturation due to specular reflection or a peaky spectrum. In this paper, we propose a restoration method for saturated hyperspectral signals. Our algorithm is based on principal component analysis to obtain the reconstruction basis and then solve a linear constrained least square problem to calculate the coefficients of each basis. We discuss the problems that saturated signals might cause and apply our method to two sets of real hyperspectral images and a set of hyperspectral images with simulated saturation. The results show that our method helps increase unsupervised object detection and improves high-fidelity color reproduction.

Infrared Radiofluorescence (IR-RF) of K-Feldspar: An Interlaboratory Comparison

Infrared Radiofluorescence (IR-RF) is a relatively new method for dosimetric dating of the depositional timing of sediments. This contribution presents an interlaboratory comparison of IR-RF measurements of sedimentary feldspar from eight laboratories. A comparison of the variability of instrumental background, bleaching, saturation, and initial rise behaviour of the IR-RF signal was carried out. Two endmember samples, a naturally bleached modern dune sand sample with a zero dose and a naturally saturated sample from a Triassic sandstone (~250 Ma), were used for this interlaboratory comparison. The major findings of this study are that (1) the observed IR-RF signal keeps decreasing beyond 4000 Gy, (2) the saturated sample gives an apparent palaeodose of 1265 ± 329 Gy and (3) in most cases, the natural IR-RF signal of the modern analogue sample (resulting from natural bleaching) is higher than the signal from laboratory-induced bleaching of 6 h, using a solar simulator (SLS). In other words, the laboratory sample bleaching was unable to achieve the level of natural bleaching. The results of the investigations are discussed in detail, along with possible explanations.

Wavelet-based neurovascular coupling can predict brain abnormalities in neonatal encephalopathy

BackgroundHypoxic-ischemic encephalopathy (HIE) is a leading cause of morbidity and mortality in neonates, but quantitative methods to predict outcomes early in their course of illness remain elusive. Real-time physiologic biomarkers of neurologic injury are needed in order to predict which neonates will benefit from therapies. Neurovascular coupling (NVC) describes the correlation of neural activity with cerebral blood flow, and the degree of impairment could predict those at risk for poor outcomes. ObjectiveTo determine if neurovascular coupling (NVC) calculated in the first 24-hours of life based on wavelet transform coherence analysis (WTC) of near-infrared spectroscopy (NIRS) and amplitude-integrated electroencephalography (aEEG) can predict abnormal brain MRI in neonatal HIE. MethodsWTC analysis was performed between dynamic oscillations of simultaneously recorded aEEG and cerebral tissue oxygen saturation (SctO2) signals for the first 24 h after birth. The squared cross-wavelet coherence, R2, of the time–frequency domain described by the WTC, is a localized correlation coefficient (ranging between 0 and 1) between these two signals in the time–frequency domain. Statistical analysis was based on Monte Carlo simulation with a 95% confidence interval to identify the time–frequency areas from the WTC scalograms. Brain MRI was performed on all neonates and classified as normal or abnormal based on an accepted classification system for HIE. Wavelet metrics of % significant SctO2-aEEG coherence was compared between the normal and abnormal MRI groups. ResultThis prospective study recruited a total of 36 neonates with HIE. A total of 10 had an abnormal brain MRI while 26 had normal MRI. The analysis showed that the SctO2-aEEG coherence between the group with normal and abnormal MRI were significantly different (p = 0.0007) in a very low-frequency (VLF) range of 0.06–0.2 mHz. Using receiver operating characteristic (ROC) curves, the use of WTC-analysis of NVC had an area under the curve (AUC) of 0.808, and with a cutoff of 10% NVC. Sensitivity was 69%, specificity was 90%, positive predictive value (PPV) was 94%, and negative predictive value (NPV) was 52% for predicting brain injury on MRI. This was superior to the clinical Total Sarnat score (TSS) where AUC was 0.442 with sensitivity 61.5%, specificity 30%, PPV 75%, and NPV 31%. ConclusionNVC is a promising neurophysiological biomarker in neonates with HIE, and in our prospective cohort was superior to the clinical Total Sarnat score for prediction of abnormal brain MRI.

A Manchester-OOK Visible Light Communication System for Patient Monitoring in Intensive Care Units

Visible Light Communication (VLC) is an interesting solution in Intensive Care (IC) medical environments to, among others, prevent the spread of emerging diseases. This work presents the design of a low-cost and stable VLC transceiver system in addition to practical characterizations and experimental performance evaluations for application in IC environments. The application focuses on the transmission of Manchester-based on-off keying signals, in a proof-of-concept apparatus that makes use of the Eye Opening Penalty (EOP) metric to illustrate a comprehensive picture of the potentials of the evaluated VLC system. Parameters such as Light-Emitting Diode (LED) bias current, modulation frequency, line-of-sight link distance, and signal pattern were analyzed here. Experimental results show an outstanding behavior considering an LED bias current of 400 mA, a signal frequency of 1 MHz and a VLC transmission link length of 2.5 m. To validate our system, vital parameters as heart rate, oxygen saturation, pulse rate, respiration rate, temperature and non-intrusive blood pressure signals were transmitted for VLC links of 1.5, 5 and 15 m, which were received by a multi-parameter monitor, with EOP values of 0.89, 0.96 and 2.67 dB, respectively.

A novel self-targeting theranostic nanoplatform for photoacoustic imaging-monitored and enhanced chemo-sonodynamic therapy.

Sonodynamic therapy has attracted wide attention as a noninvasive therapy due to deep tissue penetration. However, majority sonosensitizers often suffer from poor physiological stability, rapid blood clearance and nonspecific targeting, which seriously hinders their further practical applications. Inspired by the concept of active targeting drug delivery, both dual-functional chemo-drug pemetrexed (PEM, emerges an innate affinity toward the folate receptor) and amphiphilic d-α-tocopheryl polyethylene glycol 1000 succinate (TPGS) were selected to be covalently linked by an esterase-responsive ester linkage. The synthesized self-targeting TPGS-PEM prodrug and indocyanine green (ICG) as functional motifs can be self-assembled into a TPGS-PEM-ICG nanoplatform within an aqueous medium. The TPGS-PEM-ICG nanoplatform with outstanding structural and physiological stability not only protects the sonosensitizer from reticular endothelial system clearance but also achieves active targeting drug delivery and efficient tumor enrichment. Moreover, TPGS-PEM-ICG nanoplatform can selectively recognize tumor cells and then realize on-demand drug burst release by multiple stimuli of internal lysosomal acidity, esterase and external ultrasound, which guarantee low side effects toward normal tissues and organs. It is also worth noting that our nanoplatform exhibits protruding tumor enrichment under the precise guidance of photoacoustic/fluorescence imaging. Further in vitro and in vivo experimental results well confirmed that the TPGS-PEM-ICG nanoplatform possesses enhanced chemo-sonodynamic effects. Interestingly, the highly toxic reactive oxygen species can remarkably reduce the blood oxygen saturation signal of the tumor microenvironment via precise, multifunctional and high-resolution photoacoustic imaging. Taken together, the TPGS-PEM-ICG nanoplatform can be expected to hold enormous potential for diagnosis, prognosis and targeted therapy for tumor.

Potential of Hyperspectral Thermal Infrared Spaceborne Measurements to Retrieve Ice Cloud Physical Properties: Case Study of IASI and IASI-NG

The present study aims to quantify the potential of hyperspectral thermal infrared sounders such as the Infrared Atmospheric Sounding Interferometer (IASI) and the future IASI next generation (IASI-NG) for retrieving the ice cloud layer altitude and thickness together with the ice water path. We employed the radiative transfer model Radiative Transfer for TOVS (RTTOV) to simulate cloudy radiances using parameterized ice cloud optical properties. The radiances have been computed from an ice cloud profile database coming from global operational short-range forecasts at the European Center for Medium-range Weather Forecasts (ECMWF) which encloses the normal conditions, typical variability, and extremes of the atmospheric properties over one year (Eresmaa and McNally (2014)). We performed an information content analysis based on Shannon’s formalism to determine the amount and spectral distribution of the information about ice cloud properties. Based on this analysis, a retrieval algorithm has been developed and tested on the profile database. We considered the signal-to-noise ratio of each specific instrument and the non-retrieved atmospheric and surface parameter errors. This study brings evidence that the observing system provides information on the ice water path (IWP) as well as on the layer altitude and thickness with a convergence rate up to 95% and expected errors that decrease with cloud opacity until the signal saturation is reached (satisfying retrievals are achieved for clouds whose IWP is between about 1 and 300 g/m2).