Short Acquisition Time Research Articles

Exploring the effect of relative humidity on dynamic evolution of flax fibre’s microfibril angle through in situ tensile tests under synchrotron X-ray diffraction

Tensile properties of elementary flax fibres were investigated through in situ Synchrotron X-ray diffraction in order to understand the effect of tensile loading, on the internal reorganisation of crystalline cellulose; for the first time, these experiments were conducted for different RH conditions. Synchrotron radiation experiments were considered under reduced spot size and short acquisition times to quantify the variation of cellulose microfibril angle (MFA) in a single fibre during tensile loading, while limiting the fibre damage during X-ray exposure. The acquisitions were possible at various relative humidity (RH) conditions (from 25 % to 92 %) in order to quantify the effects of different hygro-mechanical actions upon elementary flax fibres. The results show that the MFA decreases with the increase of the applied loading, indicating a partial realignment of the cellulose microfibrils with the loading axis. The MFA at fracture point shows a decrease between − 11 and − 15 % compared to the initial MFA at all relative humidity conditions studied. The strain at break of the fibres increases with increasing relative humidity. This mechanical behaviour shows the plasticizing effect of water on the non-cellulosic amorphous matrix of cell wall.

Space and Time Coherent Mapping for Subcellular Resolution of Imaging Mass Spectrometry.

Space and time coherent mapping (STCM) is a technology developed in our laboratory for improved matrix-assisted laser desorption ionization (MALDI) time of flight (TOF) imaging mass spectrometry (IMS). STCM excels in high spatial resolutions, which probe-based scanning methods cannot attain in conventional MALDI IMS. By replacing a scanning probe with a large field laser beam, focusing ion optics, and position-sensitive detectors, STCM tracks the entire flight trajectories of individual ions throughout the ionization process and visualizes the ionization site on the sample surface with a subcellular scale of precision and a substantially short acquisition time. Results obtained in thinly sectioned leech segmental ganglia and epididymis demonstrate that STCM IMS is highly suited for (1) imaging bioactive lipid messengers such as endocannabinoids and the mediators of neuronal activities in situ with spatial resolution sufficient to detail subcellular localization, (2) integrating resultant images in mass spectrometry to optically defined cell anatomy, and (3) assembling a stack of ion maps derived from mass spectra for cluster analysis. We propose that STCM IMS is the choice over a probe-based scanning mass spectrometer for high-resolution single-cell molecular imaging.

Classification of image encoded SSVEP-based EEG signals using Convolutional Neural Networks

Brain–Computer Interfaces (BCI) systems based on electroencephalography (EEG) signals are experiencing a rapid development, counting with a number of methods, mainly from signal processing and machine learning areas. Although important results have been achieved, a robust performance is still a very challenging task, mainly considering high intra- and inter-subject variability in EEG data and long acquisition time intervals. Recently, Deep Learning methods, such as the Convolutional Neural Networks (CNNs), are being used in BCI systems in search of a performance improvement. However, the straightforward use of EEG data, without any processing step, may limit the full potential of 2D-kernels in CNNs. In light of this, in this work, we consider for classification with 2D-kernel-based CNNs the problem of encoding EEG data to images as a pre-processing stage, which includes the Gramian Angular Difference and Summation Fields, Markov Transition Fields and Recurrence Plots. Additionally, a comparative analysis using a selection of CNNs is performed. Results show a favorable performance for the proposed method, pointing towards a robust BCI system using cross-subject data, with short acquisition time interval.

Optimization of Preprocedural Full-cycle Computed Tomography in Patients Referred for Transcatheter Tricuspid Valve Repair: Test Bolus Versus Bolus Tracking.

Advancements in transcatheter mitral and tricuspid valve repair have resulted in growing demands in preprocedural computed tomography (CT) imaging. Due to the introduction of multidetector CT (MDCT), shorter acquisition times as well as high rates of heart failure and arrhythmias in this specific patient population, optimal synchronization between the passage of contrast agent and data acquisition is mandatory. There is no consensus on which acquisition technique should be used in this patient population. We aimed to optimize our preprocedural CT protocol comparing bolus tracking (BT) and test bolus (TB) techniques. We performed a retrospective analysis on 151 patients referred for full-cycle MDCT evaluation for transcatheter tricuspid valve repair comparing BT with TB (BT n=75 TB n=75). Contrast-to-noise ratios (CNR) were obtained. Demographic data, laboratory, electrocardiographic, and transthoracic echocardiography/transoesophageal echocardiography parameters were collected from electronic health records. Also, the volume of contrast agent and saline chaser and radiation dose length product and milliampere seconds were collected. BT and TB resulted in comparable CNR (BT: 0.47 [0.34 to 0.98]; TB: 0.51 [0.41 to 1.40]; P =0.1). BT was associated with a shorter scan duration (BT: 8.3min [4.1 to 24.4]; TB: 13.9min [6.2 to 41.4]; P <0.001), less radiation in terms of dose length product (BT: 1186±585; TB: 1383±679, P =0.04), and lower total volume administration (BT: 101mL [63 to 16]; TB: 114mL [71 to 154]; P <0.001). In patients with severely impaired ejection fraction (left ventricular ejection fraction [LVEF] ≤35%; n=65 [TB n=31; BT n=34]) using the TB technique yielded significantly better image quality in terms of CNR (TB=0.57 [0.41 to 1.07); BT=0.41 [0.34 to 0.65]; P =0.02). In patients with impaired LVEF (LVEF≤35%), the TB technique yielded significantly superior image quality and may be the preferred approach in this specific patient population. BT showed advantages in terms of shorter duration, less radiation, and lower contrast agent volume.

Spatiotemporal encoding MRI using subspace-constrained sampling and locally-low-rank regularization: Applications to diffusion weighted and diffusion kurtosis imaging of human brain and prostate

The benefits of performing locally low-rank (LLR) reconstructions on subsampled diffusion weighted and diffusion kurtosis imaging data employing spatiotemporal encoding (SPEN) methods, is investigated. SPEN allows for self-referenced correction of motion-induced phase errors in case of interleaved diffusion-oriented acquisitions, and allows one to overcome distortions otherwise observed along EPI's phase-encoded dimension. In combination with LLR-based reconstructions of the pooled imaging data and with a joint subsampling of b-weighted and interleaved images, additional improvements in terms of sensitivity as well as shortened acquisition times are demonstrated, without noticeable penalties. Details on how the LLR-regularized, subspace-constrained image reconstructions were adapted to SPEN are given; the improvements introduced by adopting these reconstruction frameworks for the accelerated acquisition of diffusivity and of kurtosis imaging data in both relatively homogeneous regions like the human brain and in more challenging regions like the human prostate, are presented and discussed within the context of similar efforts in the field.

Predicting 4D liver MRI for MR-guided interventions.

Organ motion poses an unresolved challenge in image-guided interventions like radiation therapy, biopsies or tumor ablation. In the pursuit of solving this problem, the research field of time-resolved volumetric magnetic resonance imaging (4D MRI) has evolved. However, current techniques are unsuitable for most interventional settings because they lack sufficient temporal and/or spatial resolution or have long acquisition times. In this work, we propose a novel approach for real-time, high-resolution 4D MRI with large fields of view for MR-guided interventions. To this end, we propose a network-agnostic, end-to-end trainable, deep learning formulation that enables the prediction of a 4D liver MRI with respiratory states from a live 2D navigator MRI. Our method can be used in two ways: First, it can reconstruct high quality fast (near real-time) 4D MRI with high resolution (209×128×128 matrix size with isotropic 1.8mm voxel size and 0.6s/volume) given a dynamic interventional 2D navigator slice for guidance during an intervention. Second, it can be used for retrospective 4D reconstruction with a temporal resolution of below 0.2s/volume for motion analysis and use in radiation therapy. We report a mean target registration error (TRE) of 1.19±0.74mm, which is below voxel size. We compare our results with a state-of-the-art retrospective 4D MRI reconstruction. Visual evaluation shows comparable quality. We compare different network architectures within our formulation. We show that small training sizes with short acquisition times down to 2 min can already achieve promising results and 24 min are sufficient for high quality results. Because our method can be readily combined with earlier time reducing methods, acquisition time can be further decreased while also limiting quality loss. We show that an end-to-end, deep learning formulation is highly promising for 4D MRI reconstruction.

Facial Scanning Accuracy with Stereophotogrammetry and Smartphone Technology in Children: A Systematic Review.

The aim of the study was to systematically review and compare the accuracy of smartphone scanners versus stereophotogrammetry technology for facial digitization in children. A systematic literature search strategy of articles published from 1 January 2010 to 30 August 2022 was adopted through a combination of Mesh terms and free text words pooled through boolean operators on the following databases: PubMed, Scopus, Web of Science, Cochrane Library, LILACS, and OpenGrey. Twenty-three articles met the inclusion criteria. Stationary stereophotogrammetry devices showed a mean accuracy that ranged from 0.087 to 0.860 mm, portable stereophotogrammetry scanners from 0.150 to 0.849 mm, and smartphones from 0.460 to 1.400 mm. Regarding the risk of bias assessment, fourteen papers showed an overall low risk, three articles had unclear risk and four articles had high risk. Although smartphones showed less performance on deep and irregular surfaces, all the analyzed devices were sufficiently accurate for clinical application. Internal depth-sensing cameras or external infrared structured-light depth-sensing cameras plugged into smartphones/tablets increased the accuracy. These devices are portable and inexpensive but require greater operator experience and patient compliance for the incremented time of acquisition. Stationary stereophotogrammetry is the gold standard for greater accuracy and shorter acquisition time, avoiding motion artifacts.

Wavelength-Tunable Quantum Absorption Spectroscopy in the Broadband Midinfrared Region

Infrared quantum absorption spectroscopy (IRQAS) enables the estimation of a sample's optical properties in the infrared region, using only a visible light source and detectors, which is technologically favorable. So far, spectral coverage of IRQAS systems has been limited to less than 1 \textmu{}m. This work reports a wavelength-tunable IRQAS system and an efficient measurement scheme to achieve broadband spectroscopy in a short acquisition time. The successful demonstration of rapid spectral measurement over a wide midinfrared window (1.9--5.2 \textmu{}m) exhibits the great potential of this technique and paves the way for the use of IRQAS in real-world applications.

A Multicast-based MAC Protocol for Improving Data Transmission Efficiency in Industrial WSNs.

In industrial WSNs, attaining the desired level of data transmission efficiency is highly challenging not only for a frequently changing network topology but also for a short data acquisition cycle time. A short data acquisition time often restrains a sensor MAC protocol to incorporate an effective data packet salvaging technique. Therefore, we propose a data transmission technique in which a sending node multicasts data packets to all candidate parents including its primary parent. As a result, the necessity of data retransmission attempts is totally avoided, which greatly improves the data transmission efficiency in industrial WSNs. By simulation experiments, we have shown that the proposed multicast-based MAC protocol surpasses all the competing MAC protocols regarding the successful data packet delivery and power saving with a significant margin

Curvelet Transform-Based Sparsity Promoting Algorithm for Fast Ultrasound Localization Microscopy.

Ultrasound localization microscopy (ULM) based on microbubble (MB) localization was recently introduced to overcome the resolution limit of conventional ultrasound. However, ULM is currently challenged by the requirement for long data acquisition times to accumulate adequate MB events to fully reconstruct vasculature. In this study, we present a curvelet transform-based sparsity promoting (CTSP) algorithm that improves ULM imaging speed by recovering missing MB localization signal from data with very short acquisition times. CTSP was first validated in a simulated microvessel model, followed by the chicken embryo chorioallantoic membrane (CAM), and finally, in the mouse brain. In the simulated microvessel study, CTSP robustly recovered the vessel model to achieve an 86.94% vessel filling percentage from a corrupted image with only 4.78% of the true vessel pixels. In the chicken embryo CAM study, CTSP effectively recovered the missing MB signal within the vasculature, leading to marked improvement in ULM imaging quality with a very short data acquisition. Taking the optical image as reference, the vessel filling percentage increased from 2.7% to 42.2% using 50ms of data acquisition after applying CTSP. CTSP used 80% less time to achieve the same 90% maximum saturation level as compared with conventional MB localization. We also applied CTSP on the microvessel flow speed maps and found that CTSP was able to use only 1.6s of microbubble data to recover flow speed images that have similar qualities as those constructed using 33.6s of data. In the mouse brain study, CTSP was able to reconstruct the majority of the cerebral vasculature using 1–2s of data acquisition. Additionally, CTSP only needed 3.2s of microbubble data to generate flow velocity maps that are comparable to those using 129.6s of data. These results suggest that CTSP can facilitate fast and robust ULM imaging especially under the circumstances of inadequate microbubble localizations.

Monitoring lava dome extrusion of Merapi Volcano during 2018-2019, using low-cost UAV application

Merapi volcano has a well-known eruption type, namely Merapi type, in which an extruded lava dome collapses and is accompanied by pyroclastic density current (PDC). This type of eruption makes morphological monitoring of the lava dome crucial in the hazard mitigation process. After the VEI 4 eruption in 2010, a new lava dome of Merapi appeared on top of the 2010 lava dome in August 2018 and continuously grew. In November 2019, the lava dome started to collapse outward the crater area. We reported the lava dome morphological monitoring using a UAV (Unmanned Aerial Vehicle) photogrammetry conducted from August 2018 to February 2019. This UAV monitoring provides processed aerial photo data in Digital Terrain Model (DTM) and orthophoto with low operating costs and short data acquisition time. The lava domes erupted from the same eruptive canter within this period and grew evenly in all directions. The 2018-2019 Merapi lava dome has basal ratio of 0.183 to 0.290 with height of 11 to 41 m, respectively. Volume changed from 33,623 m3 in August 2018 to 658,075 m3 in February 2019, suggesting growth rate at ~3,500 m3/day. The lava base filled the crater base area (0.21 km2) and started to collapse outward in November 2019.

Tracked 3D ultrasound and deep neural network-based thyroid segmentation reduce interobserver variability in thyroid volumetry.

Thyroid volumetry is crucial in the diagnosis, treatment, and monitoring of thyroid diseases. However, conventional thyroid volumetry with 2D ultrasound is highly operator-dependent. This study compares 2D and tracked 3D ultrasound with an automatic thyroid segmentation based on a deep neural network regarding inter- and intraobserver variability, time, and accuracy. Volume reference was MRI. 28 healthy volunteers (24—50 a) were scanned with 2D and 3D ultrasound (and by MRI) by three physicians (MD 1, 2, 3) with different experience levels (6, 4, and 1 a). In the 2D scans, the thyroid lobe volumes were calculated with the ellipsoid formula. A convolutional deep neural network (CNN) automatically segmented the 3D thyroid lobes. 26, 6, and 6 random lobe scans were used for training, validation, and testing, respectively. On MRI (T1 VIBE sequence) the thyroid was manually segmented by an experienced MD. MRI thyroid volumes ranged from 2.8 to 16.7ml (mean 7.4, SD 3.05). The CNN was trained to obtain an average Dice score of 0.94. The interobserver variability comparing two MDs showed mean differences for 2D and 3D respectively of 0.58 to 0.52ml (MD1 vs. 2), −1.33 to −0.17ml (MD1 vs. 3) and −1.89 to −0.70ml (MD2 vs. 3). Paired samples t-tests showed significant differences for 2D (p = .140, p = .002 and p = .002) and none for 3D (p = .176, p = .722 and p = .057). Intraobsever variability was similar for 2D and 3D ultrasound. Comparison of ultrasound volumes and MRI volumes showed a significant difference for the 2D volumetry of all MDs (p = .002, p = .009, p <.001), and no significant difference for 3D ultrasound (p = .292, p = .686, p = 0.091). Acquisition time was significantly shorter for 3D ultrasound. Tracked 3D ultrasound combined with a CNN segmentation significantly reduces interobserver variability in thyroid volumetry and increases the accuracy of the measurements with shorter acquisition times.

Applications of a novel electron energy filter combined with a hybrid-pixel direct electron detector for the analysis of functional oxides by STEM/EELS and energy-filtered imaging

The performance and suitability of a new electron energy filter in combination with a hybrid pixel, direct electron detector for analytical (scanning) transmission electron microscopy are demonstrated using four examples. The STEM-EELS capabilities of the CEOS Energy Filtering and Imaging Device (CEFID) were tested with focus on weak signals and high spatio-temporal resolution. A multiferroic, multilayer structure of REMnO3 (RE = Yb, Er, Tb, Y), grown on yttria-stabilized zirconia (YSZ), is used to exemplify that this new instrumental setup produces valuable electron energy-loss spectroscopy (EELS) data at high energy losses even when using short acquisition times, providing detailed chemical information about the interfaces in this complex multilayer sample. Another functional oxide, namely a ferromagnetic La2NiMnO6 thin film grown on SrTiO3, demonstrates that atomically resolved spectrum images can be recorded, using short dwell times and moderate beam currents in order to warrant the integrity of the sample. In a third example, inhomogeneously Er-doped YSZ shows by EELS spectrum imaging that elements at low concentrations can be detected semi-quantitatively, uncovering the expected layered Er distribution but revealing substantial interdiffusion. In a final example, we simply demonstrate that the hybrid pixel detector in combination with the energy filter can also be used for energy-filtered imaging and thus for elemental mapping complementary to EELS in scanning transmission mode.

Unmixing multi-spectral electrical impedance tomography (EIT) predicts clinical-standard controlled attenuation parameter (CAP) for nonalcoholic fatty liver disease classification: a feasibility study.

Here, we tested the feasibility of predicting CAP with multi-spectral EIT. Conductivity and CAP were acquired from nonalcoholic fatty liver disease patients using a portable EIT system and vibration-controlled transient elastography (VCTE). We then used frequency-difference conductivity and waist-over-height as prediction features to estimate CAP and found an adj. R2 of 0.92. We further developed a novel prediction method by incorporating EIT spectral unmixing reconstruction and demonstrated an improvement in CAP estimation. Last, we optimized the EIT acquisition process by minimizing the total variance of the CAP estimator. Clinical Relevance: EIT can estimate clinical-standard liver disease classification. This portable EIT system is potentially cost-effective and self-administrable with short acquisition time (3 mins), while VCTE are costly and usually requires a trained personnel to operate with longer acquisition time (5-10 mins).

Evaluation of pediatric malignancies using total-body PET/CT with half-dose [18F]-FDG.

To explore the impact of a true half dose of [18F]-FDG on image quality in pediatric oncological patients undergoing total-body PET/CT and investigate short acquisition times with half-dose injected activity. One hundred pediatric oncological patients who underwent total-body PET/CT using the uEXPLORER scanner after receiving a true half dose of [18F]-FDG (1.85MBq/kg) were retrospectively enrolled. The PET images were first reconstructed using complete 600-s data and then split into 300-s, 180-s, 60-s, 40-s, and 20-s duration groups (G600 to G20). The subjective analysis was performed using 5-point Likert scales. Objective quantitative metrics included the maximum standard uptake value (SUVmax), SUVmean, standard deviation (SD), signal-to-noise ratio (SNR), and SNRnorm of the background. The variabilities in lesion SUVmean, SUVmax, and tumor-to-background ratio (TBR) were also calculated. The overall image quality scores in the G600, G300, G180, and G60 groups were 4.9 ± 0.2, 4.9 ± 0.3, 4.4 ± 0.5, and 3.5 ± 0.5 points, respectively. All the lesions identified in the half-dose images were localized in the G60 images, while 56% of the lesions could be clearly identified in the G20 images. With reduced acquisition time, the SUVmax and SD of the backgrounds were gradually increased, while the TBR values showed no statistically significant differences among the groups (all p > 0.1). Using the half-dose images as a reference, the variability in the lesion SUVmax gradually increased from the G180 to G20 images, while the lesion SUVmean remained stable across all age groups. SNRnorm was highly negatively correlated with age. Total-body PET/CT with a half dose of [18F]-FDG (1.85MBq/kg, estimated whole-body effective dose: 1.76-2.57mSv) achieved good performance in pediatric patients, with sufficient image quality and good lesion conspicuity. Sufficient image quality and lesion conspicuity could be maintained at a fast scanning time of 60s with half-dose activity.

Inline-Feasible Contrast Separation in Luminescence Imaging for Silicon Solar Cells

We present an article about separating contrasts in luminescence images of silicon solar cells for industrial application, i.e., in very short measurement times significantly below one second. The well-known method “Coupled Determination of Dark Saturation Current Density and Series Resistance” by Glatthaar <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> is optimized to drastically decrease the required exposure time. The correction using an image under short-circuit conditions is omitted. Simulations with Quokka3, which give insight into the mechanisms of contrast separation, are performed. The operating points at which the images are acquired are adjusted allowing short data acquisition times. The optimized method decreases the necessary exposure time by more than a factor of 6 to 160 ms for a multicrystalline silicon passivated emitter and rear cell (PERC) solar cell. The quality regarding contrast separation can be maintained.

Validation of a Saliency Map for Assessing Image Quality in Nuclear Medicine: Experimental Study Outcomes

Recently, the use of saliency maps to evaluate the image quality of nuclear medicine images has been reported. However, that study only compared qualitative visual evaluations and did not perform a quantitative assessment. The study’s aim was to demonstrate the possibility of using saliency maps (calculated from intensity and flicker) to assess nuclear medicine image quality by comparison with the evaluator’s gaze data obtained from an eye-tracking device. We created 972 positron emission tomography images by changing the position of the hot sphere, imaging time, and number of iterations in the iterative reconstructions. Pearson’s correlation coefficient between the saliency map calculated from each image and the evaluator’s gaze data during image presentation was calculated. A strong correlation (r ≥ 0.94) was observed between the saliency map (intensity) and the evaluator’s gaze data. This trend was also observed in images obtained from a clinical device. For short acquisition times, the gaze to the hot sphere position was higher for images with fewer iterations during the iterative reconstruction. However, no differences in iterations were found when the acquisition time increased. Saliency by flicker could be applied to clinical images without preprocessing, although compared with the gaze image, it increased slowly.

Optimization of scan parameters to reduce acquisition time for RESOLVE-based diffusion kurtosis imaging (DKI) in nasopharyngeal carcinoma (NPC).

To shorten acquisition time of readout segmentation of long variable echo trains (RESOLVE)-based diffusion kurtosis imaging (DKI) via Readout Partial Fourier (RPF) and b-value combinations. The RESOLVE-based DKI images of 38 patients with nasopharyngeal carcinoma (NPC) were prospectively enrolled. For RESOLVE-based DKI images with 5/8 RPF and without RPF, objective and subjective evaluations of image quality were performed. A total of nine groups with different b-value combinations were simulated, and the influence of different b-value combinations for RESOLVE-RPF-based DKI sequences was assessed using the intraclass correlation coefficient (ICC). The mean values of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in DKI images without RPF were higher than those with 5/8 RPF (252.9 ± 77.7 vs 247.3 ± 85.5 and 5.8 ± 2.8 vs 5.4 ± 2.3, respectively), but not significantly (p = 0.460 and p = 0.180, respectively). In comparing the ICCs between nine groups of different b-value combinations in RESOLVE-RPF-based DKI, group (200, 800, 2000 s/mm2), group (200, 400, 800, 2000 s/mm2) and group (200, 800, 1500, 2000 s/mm2) were not significantly different (p > 0.001) and showed excellent agreement (0.81-1.00) with that of group (200, 400, 800, 1500, 2000 s/mm2). Using b-value optimization and RPF technology, the group with RPF (200, 400, 800, 2000 s/mm2) showed a 56% reduced scanning compared with the group without RPF (200, 400, 800, 1500, 2000 s/mm2; 3 min 46 s vs 8 min 31 s, respectively). DKI with RPF did not significantly affect image quality, but both RPF and different b-value combinations can affect the scanning time. The combination of RPF and b-value optimization can ensure the stability of DKI parameters and reduce the scanning time by 56%. This work is to optimize scan parameters, e.g. RPF and b-value combinations, to reduce acquisition time for RESOLVE-based DKI in NPC. To our knowledge, the effect of RESOLVE-RPF and b-value combinations on DKI has not been reported.

A general overview and comparative interpretation on element‐specific X‐ray spectroscopy techniques:XPS,XAS,andXRS

AbstractX‐ray photoelectron spectroscopy (XPS), X‐ray absorption spectroscopy (XAS) and X‐ray Raman scattering (XRS) spectroscopy are the element‐specific tools providing local electronic and chemical structure insights. XPS is widely used for qualitative/quantitative surface analysis of solids and replaced by synchrotron‐based ambient pressure‐XPS and hard‐XPS to benefit from the advantages of near‐ambient pressures and hard X‐rays to study complex sample environments. XAS is a well‐established soft and hard X‐ray probe to examine the coordination, spin and oxidation states in solids, liquids and gases with high resolutions and short data acquisition time. XRS, using the hard X‐rays of ~10 keV, is preferred to conventional XAS and XPS in the study of soft X‐ray absorption edges such as C, O, Li K‐edges bulk‐sensitively in vacuum‐free medium for energy storage systems during working operations, inner Earth elements under realistic conditions, probing chemical and biological reactions in the liquid phase, C speciation in archeological and paleontological samples and direct tomography. In this study, first the basics of XPS, XAS, and XRS techniques with their advantages and limitations are introduced to provide a general overview. In the Results and Discussion, the particular emphasis is given to the comparison of XPS, XAS, and XRS with the interpretation of the spectroscopic signatures for organic carbonate‐based electrolytes. The computed C 1 s binding energy shifts for ethylene carbonate (EC), propylene carbonate (PC), dimethyl carbonate (DMC), and diethyl carbonate (DEC) are presented to discuss the XPS peak assignments and the performed C K‐edge XRS measurements of 1 M LiPF6in DMC and EC are given for a detailed discussion of the XRS spectra. C 1 s XPS, C K‐edge XAS, and XRS of PC from the literature are discussed to interpret the spectra of each technique comparatively.

Research and Development of Preclinical Overhauser-Enhanced Magnetic Resonance Imaging.

Significance: Imaging free radicals, including reactive oxygen species and reactive nitrogen species, can be useful for understanding the pathology of diseases in animal disease models, as they are related to various physiological functions or diseases. Among the methods used for imaging free radicals, Overhauser-enhanced magnetic resonance imaging (OMRI) has a short image acquisition time and high spatial resolution. Therefore, OMRI is used to obtain various biological parameters. In this study, we review the methodology for improving the biological OMRI system and its applications. Recent Advances: The sensitivity of OMRI systems has been enhanced significantly to allow the visualization of various biological parameters, such as redox state, partial oxygen pressure, and pH, in different body parts of small animals, using spin probes. Furthermore, both endogenous free radicals and exogenous free radicals present in drugs can be visualized using OMRI. Critical Issues: To acquire accurate biological parameters at a high resolution, it is essential to increase the electron paramagnetic resonance (EPR) excitation efficiency and achieve a high enhancement factor. In addition, the size and magnetic field strength also need to be optimized for the measurement target. Future Directions: The advancement of in vivo OMRI techniques will be useful for understanding the pathology, diagnosis, and evaluation of therapeutic effects of drugs in various disease models. Antioxid. Redox Signal. 37, 1094-1110.