Diffusion Measurements Research Articles

Metabolic changes assessed by 1H MR spectroscopy in the corpus callosum of post-COVID patients

ObjectiveMany patients with long COVID experience neurological and psychological symptoms. Signal abnormalities on MR images in the corpus callosum have been reported. Knowledge about the metabolic profile in the splenium of the corpus callosum (CCS) may contribute to a better understanding of the pathophysiology of long COVID.Materials and methodsEighty-one subjects underwent proton MR spectroscopy examination. The metabolic concentrations of total N-acetylaspartate (NAA), choline-containing compounds (Cho), total creatine (Cr), myo-inositol (mI), and NAA/Cho in the CCS were statistically compared in the group of patients containing 58 subjects with positive IgG COVID-19 antibodies or positive SARS-CoV-2 qPCR test at least two months before the MR and the group of healthy controls containing 23 subjects with negative IgG antibodies.ResultsAn age-dependent effect of SARS-CoV-2 on Cho concentrations in the CCS has been observed. Considering the subjective threshold of age = 40 years, older patients showed significantly increased Cho concentrations in the CCS than older healthy controls (p = 0.02). NAA, Cr, and mI were unchanged. All metabolite concentrations in the CCS of younger post-COVID-19 patients remained unaffected by SARS-CoV-2. Cho did not show any difference between symptomatic and asymptomatic patients (p = 0.91).DiscussionOur results suggest that SARS-CoV-2 disproportionately increases Cho concentration in the CCS among older post-COVID-19 patients compared to younger ones. The observed changes in Cho may be related to the microstructural reorganization in the CCS also reported in diffusion measurements rather than increased membrane turnover. These changes do not seem to be related to neuropsychological problems of the post-COVID-19 patients. Further metabolic studies are recommended to confirm these observations.

Taylor dispersion analysis for measurement of diffusivity and size of gadolinium-based contrast agents

Gadolinium-based contrast agents (GBCA) are complexes of a Gadolinium metal center and a linear or macrocyclic polyamino-carboxylic acid chelating agent. These agents are employed to enhance the visibility of deep abnormalities through MRI techniques. Knowing the precise dimensions of various GBCA is key parameter for understanding their in-vivo and pharmaco-kinetic behaviors, their diffusivity, as well as their relaxivity. However, conventional size characterization techniques fall short when dealing with these tiny molecules (≤1 nm). In this work, we propose to determine the size and diffusivity of gadolinium-based contrast agents using Taylor dispersion analysis (TDA). TDA provided a reliable measurement of the hydrodynamic diameter and the diffusion coefficient. The obtained results were compared to DOSY NMR (Diffusion-ordered Nuclear Magnetic Resonance Spectroscopy) and DFT (Density Functional Theory).

Functional and structural maturation of auditory cortex from 2 months to 2 years old.

In school-age children, the myelination of the auditory radiation thalamocortical pathway is associated with the latency of auditory evoked responses, with the myelination of thalamocortical axons facilitating the rapid propagation of acoustic information. Little is known regarding this auditory system function-structure association in infants and toddlers. The present study tested the hypothesis that maturation of auditory radiation white-matter microstructure (e.g., fractional anisotropy (FA); measured using diffusion-weighted MRI) is associated with the latency of the infant auditory response (P2m measured using magnetoencephalography, MEG) in a cross-sectional (2 to 24 months) as well as longitudinal cohort (2 to 29 months) of typically developing infants and toddlers. In the cross-sectional sample, non-linear maturation of P2m latency and auditory radiation diffusion measures were observed. After removing the variance associated with age in both P2m latency and auditory radiation diffusion measures, auditory radiation still accounted for significant variance in P2m latency. In the longitudinal sample, latency and FA associations could be observed at the level of a single child. Findings provide strong support for a contribution of auditory radiation white matter to rapid cortical auditory encoding processes in infants.

First operation of a multi-channel Q-Pix prototype: measuring transverse electron diffusion in a gas time projection chamber

We report measurements of the transverse diffusion of electrons in P-10 gas (90% Ar, 10% CH4) in a laboratory-scale time projection chamber (TPC) utilizing a novel pixelated signal capture and digitization technique known as Q-Pix. The Q-Pix method incorporates a precision switched integrating transimpedance amplifier whose output is compared to a threshold voltage. Upon reaching the threshold, a comparator sends a 'reset' signal, initiating a discharge of the integrating capacitor. The time difference between successive resets is inversely proportional to the average current at the pixel in that time interval, and the number of resets is directly proportional to the total collected charge. We developed a 16-channel Q-Pix prototype fabricated from commercial off-the-shelf components and coupled them to 16 concentric annular anode electrodes to measure the spatial extent of the electron swarm that reaches the anode after drifting through the uniform field of the TPC. The swarm is produced at a gold photocathode using pulsed UV light. The measured transverse diffusion agrees with simulations in PyBoltz across a range of operating pressures (200–1500 Torr). These results demonstrate that a Q-Pix readout can successfully reconstruct the ionization topology in a TPC.

Self‐Made Equipment for Automatic Methane Diffusion and Ebullition Measurements From Aquatic Environments

AbstractFreshwater ecosystems are believed to account for about half of global methane emissions, but this estimate is uncertain due to few measurements in some geographical regions and most important for our purposes, large local variations. We propose a simple, cheap (<200€), and effective solution to the urgent need for equipment that can provide accurate data on methane emission at high spatial and temporal resolution for many days, across many ecosystems and regions, and with limited inspection. A low‐cost metal oxide semiconductor sensor, placed in a floating chamber equipped with an air pump to flush the chamber's headspace at regular intervals, provides frequent and accurate high‐resolution measurements of diffusive and ebullitive methane emissions from lakes and rivers. We made several improvements that yield more useful data and enable the setup to operate for several days without visual inspection. To test the accuracy of the equipment, we compared its measurements of methane emission to parallel measurements by an expensive, commercially available laser sensor. The correspondence was excellent (R2 ≥ 0.94) and the deviation of measurements was minimal at fluxes within ranges encountered in the field. We also designed an R‐package (FluxSeparator), which associates the large sensor‐generated data sets with diffusive and ebullitive flux activity. Both the sensor setup and the R‐package are flexible and have been made publicly available to encourage others to use and further improve the equipment and calculations.

The SPECTRAL Perfusion Arm Clamping dAtaset (SPECTRALPACA) for video-rate functional imaging of the skin

Spectral imaging has the potential to become a key technique in interventional medicine as it unveils much richer optical information compared to conventional RBG (red, green, and blue)-based imaging. Thus allowing for high-resolution functional tissue analysis in real time. Its higher information density particularly shows promise for the development of powerful perfusion monitoring methods for clinical use. However, even though in vivo validation of such methods is crucial for their clinical translation, the biomedical field suffers from a lack of publicly available datasets for this purpose. Closing this gap, we generated the SPECTRAL Perfusion Arm Clamping dAtaset (SPECTRALPACA). It comprises ten spectral videos (∼20 Hz, approx. 20,000 frames each) systematically recorded of the hands of ten healthy human participants in different functional states. We paired each spectral video with concisely tracked regions of interest, and corresponding diffuse reflectance measurements recorded with a spectrometer. Providing the first openly accessible in human spectral video dataset for perfusion monitoring, our work facilitates the development and validation of new functional imaging methods.

Obesity and diffusion-weighted imaging of subcortical grey matter in young and older adults

Obesity and hypothalamic inflammation are causally related. It is unclear whether this neuroinflammation precedes or results from obesity. Animal studies show that an increase in food intake can lead to hypothalamic inflammation, but hypothalamic inflammation can create a feedback loop that further increases food intake. Internal and external factors mediate patterns of food intake and how it can affect the hypothalamus. Measures of water diffusivity in magnetic resonance imaging of the brain such as fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD) are associated with grey matter inflammation. Here, we investigated how those measures are associated with obesity-related variables in groups of young and older adults. We found relationships between decreased diffusivity and obesity markers in young adults. In older adults, obesity and comorbidities were also related to significant changes in diffusivity. Here, diffusivity was strongly associated with body mass index (BMI) and blood levels of C-reactive protein (CRP) in multiple subcortical regions, rather than only the hypothalamus. Our results suggest that diffusivity measures can be used to investigate obesity-associated changes in the brain that can potentially reflect neuroinflammation. The connection seen between subcortical inflammation and obesity opens the conversation on preventative interventions needed to reduce the effects of obesity at all stages in life.

The relationship between parameters measured using intravoxel incoherent motion and dynamic contrast-enhanced MRI in patients with breast cancer undergoing neoadjuvant chemotherapy: a longitudinal cohort study.

The primary aim of this study was to explore whether intravoxel incoherent motion (IVIM) can offer a contrast-agent-free alternative to dynamic contrast-enhanced (DCE)-MRI for measuring breast tumor perfusion. The secondary aim was to investigate the relationship between tissue diffusion measures from DWI and DCE-MRI measures of the tissue interstitial and extracellular volume fractions. A total of 108 paired DWI and DCE-MRI scans were acquired at 1.5 T from 40 patients with primary breast cancer (median age: 44.5 years) before and during neoadjuvant chemotherapy (NACT). DWI parameters included apparent diffusion coefficient (ADC), tissue diffusion (Dt), pseudo-diffusion coefficient (Dp), perfused fraction (f), and the product f×Dp (microvascular blood flow). DCE-MRI parameters included blood flow (Fb), blood volume fraction (vb), interstitial volume fraction (ve) and extracellular volume fraction (vd). All were extracted from three tumor regions of interest (whole-tumor, ADC cold-spot, and DCE-MRI hot-spot) at three MRI visits: pre-treatment, after one, and three cycles of NACT. Spearman's rank correlation was used for assessing between-subject correlations (r), while repeated measures correlation was employed to assess within-subject correlations (rrm) across visits between DWI and DCE-MRI parameters in each region. No statistically significant between-subject or within-subject correlation was found between the perfusion parameters estimated by IVIM and DCE-MRI (f versus vb and f×Dp versus Fb; P=0.07-0.81). Significant moderate positive between-subject and within-subject correlations were observed between ADC and ve (r=0.461, rrm=0.597) and between Dt and ve (r=0.405, rrm=0.514) as well as moderate positive within-subject correlations between ADC and vd and between Dt and vd (rrm=0.619 and 0.564, respectively) in the whole-tumor region. No correlations were observed between the perfusion parameters estimated by IVIM and DCE-MRI. This may be attributed to imprecise estimates of fxDp and vb, or an underlying difference in what IVIM and DCE-MRI measure. Care should be taken when interpreting the IVIM parameters (f and f×Dp) as surrogates for those measured using DCE-MRI. However, the moderate positive correlations found between ADC and Dt and the DCE-MRI parameters ve and vd confirms the expectation that as the interstitial and extracellular volume fractions increase, water diffusion increases.

Ultrafast nanometric resolution spatiotemporal measurement of ambipolar diffusivity and carrier-phonon coupling in doped and undoped silicon

Understanding and determination of the ambipolar diffusivity of a semiconductor is fundamental for predicting device behavior and optimizing its performance. Ultrafast pump-probe measurements allow for the determination of energy carrier dynamics with sub-picosecond resolution. Due to the inherent diffusive nature of carriers, measurements with a high spatial resolution are needed, in addition to the traditional pump-probe system, to determine not only the carrier dynamics but also the spatial extent caused by carrier diffusion as well. In this work, a spatiotemporal measurement system with ultrafast temporal and nanometric spatial resolution, together with a comprehensive transport model, is used to determine the ambipolar diffusivity and carrier-phonon energy coupling time in both undoped and doped silicon. The results show that as the carrier density increases, the measured ambipolar diffusivity decreases with minimal variation in the carrier-phonon energy coupling time. In general, this work demonstrates an optical-based method for determining ambipolar diffusivity in a semiconductor material.

PyDesigner v1.0: A Pythonic Implementation of the DESIGNER Pipeline for Diffusion Magnetic Resonance Imaging.

PyDesigner is a Python-based software package based on the original Diffusion parameter EStImation with Gibbs and NoisE Removal (DESIGNER) pipeline (Dv1) for dMRI preprocessing and tensor estimation. This software is openly provided for non-commercial research and may not be used for clinical care. PyDesigner combines tools from FSL and MRtrix3 to perform denoising, Gibbs ringing correction, eddy current motion correction, brain masking, image smoothing, and Rician bias correction to optimize the estimation of multiple diffusion measures. It can be used across platforms on Windows, Mac, and Linux to accurately derive commonly used metrics from DKI, DTI, WMTI, FBI, and FBWM datasets as well as tractography ODFs and .fib files. It is also file-format agnostic, accepting inputs in the form of .nii, .nii.gz, .mif, and dicom format. User-friendly and easy to install, this software also outputs quality control metrics illustrating signal-to-noise ratio graphs, outlier voxels, and head motion to evaluate data integrity. Additionally, this dMRI processing pipeline supports multiple echo-time dataset processing and features pipeline customization, allowing the user to specify which processes are employed and which outputs are produced to meet a variety of user needs.

Erythrocyte membrane fatty acid concentrations and myelin integrity in young people at ultra-high risk of psychosis

Decreased white matter (WM) integrity and disturbance in fatty acid composition have been reported in individuals at ultra-high risk of psychosis (UHR). The current study is the first to investigate both WM integrity and erythrocyte membrane polyunsaturated fatty acid (PUFA) levels as potential risk biomarkers for persistent UHR status, and global functioning in UHR individuals. Forty UHR individuals were analysed at baseline for erythrocyte membrane PUFA concentrates. Tract-based spatial statistics (TBSS) was used to analyse fractional anisotropy (FA) and diffusivity measures. Measures of global functioning and psychiatric symptoms were evaluated at baseline and at 12-months. Fatty acids and WM indices did not predict functional outcomes at baseline or 12-months. Significant differences were found in FA between UHR remitters and non-remitters (individuals who no longer met UHR criteria versus those who continued to meet criteria at 12-months). Docosahexaenoic acid (DHA) was found to be a significant predictor of UHR status at 12-months, as was the interaction between the sum of ώ-3 and whole brain FA, and the interaction between the right anterior limb of the internal capsule and the sum of ώ-3. The results confirm that certain fatty acids have a unique relationship with WM integrity in UHR individuals.

Effects of Photon versus Carbon-Ion Irradiation in the Rat Cervical Spinal Cord - a Serial T2 and Diffusion-weighted Magnetic Resonance Imaging Study.

Carbon-ion irradiation is increasingly used at the skull base and spine near the radiation-sensitive spinal cord. To better characterize the invivo radiation response of the cervical spinal cord, radiogenic changes in the high-dose area were measured in rats using magnetic resonance imaging (MRI) diffusion measurements in comparison to conventional photon irradiations. In this longitudinal MRI study, we examined the gray matter (GM) of the cervical spinal cord in 16 female Sprague-Dawley rats after high-dose photon (n = 8) or carbon-ion (12C) irradiation (n = 8) and in 6 sham-exposed rats until myelopathy occurred. The differences in the diffusion pattern of the GM of the cervical spinal cord were examined until the endpoint of the study, occurrence of paresis grade II of both forelimbs was reached. In both radiation techniques, the same order of the occurrence of MR-morphological pathologies was observed - from edema formation to a blood spinal cord barrier (BSCB) disruption to paresis grade II of both forelimbs. However, carbon-ion irradiation showed a significant increase of the mean apparent diffusion coefficient (ADC; P = 0.031) with development of a BSCB disruption in the GM. Animals with paresis grade II as a late radiation response had a highly significant increase in mean ADC (P = 0.0001) after carbon-ion irradiation. At this time, a tendency was observed for higher mean ADC values in the GM after 12C irradiation as compared to photon irradiation (P = 0.059). These findings demonstrated that carbon-ion irradiation leads to greater structural damage to the GM of the rat cervical spinal cord than photon irradiation due to its higher linear energy transfer (LET) value.

The Influence of Cyclic Thermal Shocks at High Temperatures on the Microstructure, Hardness and Thermal Diffusivity of the Rene 41 Alloy.

The precipitation-hardenable nickel-based superalloy Rene 41 exhibits remarkable mechanical characteristics and high corrosion resistance at high temperatures, properties that allow it to be used in high-end applications. This research paper presents findings on the influence of thermal shocks on its microstructure, hardness, and thermal diffusivity at temperatures between 700 and 1000 °C. Solar energy was used for cyclic thermal shock tests. The samples were characterized using microhardness measurements, optical microscopic analysis, scanning electron microscopy coupled with EDS elemental chemical analysis, X-ray diffraction, and flash thermal diffusivity measurements. Structural transformations and the variation of properties were observed with an increase in the number of shocks applied at the same temperature and with temperature variation for the same number of thermal shocks.

On the relationship between viscoelasticity and water diffusion in soft biological tissues

Magnetic resonance elastography (MRE) and diffusion-weighted imaging (DWI) are complementary imaging techniques that detect disease based on viscoelasticity and water mobility, respectively. However, the relationship between viscoelasticity and water diffusion is still poorly understood, hindering the clinical translation of combined DWI-MRE markers.We used DWI-MRE to study 129 biomaterial samples including native and cross-linked collagen, glycosaminoglycans (GAGs) with different sulfation levels, and decellularized specimens of pancreas and liver, all with different proportions of solid tissue, or solid fractions. We developed a theoretical framework of the relationship between mechanical loss and tissue-water mobility based on two parameters, solid and fluid viscosity. These parameters revealed distinct DWI-MRE property clusters characterizing weak, moderate, and strong water-network interactions. Sparse networks interacting weakly with water, such as collagen or diluted decellularized tissue, resulted in marginal changes in water diffusion over increasing solid viscosity. In contrast, dense networks with larger solid fractions exhibited both free and hindered water diffusion depending on the polarity of the solid components. For example, polar and highly sulfated GAGs as well as native soft tissues hindered water diffusion despite relatively low solid viscosity.Our results suggest that two fundamental properties of tissue networks, solid fraction and network polarity, critically influence solid and fluid viscosity in biological tissues. Since clinical DWI and MRE are sensitive to these viscosity parameters, the framework we present here can be used to detect tissue remodeling and architectural changes in the setting of diagnostic imaging. Statement of significanceThe viscoelastic properties of biological tissues provide a wealth of information on the vital state of cells and host matrix. Combined measurement of viscoelasticity and water diffusion by medical imaging is sensitive to tissue microarchitecture. However, the relationship between viscoelasticity and water diffusion is still poorly understood, hindering full exploitation of these properties as a combined clinical biomarker. Therefore, we analyzed the parameter space accessible by diffusion-weighted imaging (DWI) and magnetic resonance elastography (MRE) and developed a theoretical framework for the relationship between water mobility and mechanical parameters in biomaterials. Our theory of solid material properties related to particle motion can be translated to clinical radiology using clinically established MRE and DWI.

Tracts in the limbic system show microstructural alterations post COVID-19 recovery.

Delirium, memory loss, attention deficit and fatigue are frequently reported by COVID survivors, yet the neurological pathways underlying these symptoms are not well understood. To study the possible mechanisms for these long-term sequelae after COVID-19 recovery, we investigated the microstructural properties of white matter in Indian cohorts of COVID-recovered patients and healthy controls. For the cross-sectional study presented here, we recruited 44 COVID-recovered patients and 29 healthy controls in New Delhi, India. Using deterministic whole-brain tractography on the acquired diffusion MRI scans, we traced 20 white matter tracts and compared fractional anisotropy, axial, mean and radial diffusivity between the cohorts. Our results revealed statistically significant differences (PFWE < 0.01) in the uncinate fasciculus, cingulum cingulate, cingulum hippocampus and arcuate fasciculus in COVID survivors, suggesting the presence of microstructural abnormalities. Additionally, in a subsequent subgroup analysis based on infection severity (healthy control, non-hospitalized patients and hospitalized patients), we observed a correlation between tract diffusion measures and COVID-19 infection severity. Although there were significant differences between healthy controls and infected groups, we found no significant differences between hospitalized and non-hospitalized COVID patients. Notably, the identified tracts are part of the limbic system and orbitofrontal cortex, indicating microstructural differences in neural circuits associated with memory and emotion. The observed white matter alterations in the limbic system resonate strongly with the functional deficits reported in Long COVID. Overall, our study provides additional evidence that damage to the limbic system could be a neuroimaging signature of Long COVID. The findings identify targets for follow-up studies investigating the long-term physiological and psychological impact of COVID-19.

Realization of new n = 3 and n = 4 Dion-Jacobson layered perovskite series with interlayer K+ ions and perovskite blocks stabilized by Pr3+ ions

The structural flexibility of the perovskite blocks in the Dion-Jacobson family of layered perovskite oxides has successfully resulted in the generation of KPrNan-2NbnO3n+1 and KPrCan-2Nb2Tin-2O3n+1 (n = 3, 4). The stabilization of K+ ions preferring a six coordination in the interlayer region is significant compared to the facile formation of layered perovskite oxides possessing bigger Rb+ or Cs+ ions with an eight coordination in the interlayer. The structure of the n = 3 members, KPrNaNb3O10 (S. G. Cmcm; a = 3.8858(1) Å, b = 29.6553(9) Å, c = 7.7635(3) Å) and KPrCaNb2TiO10 (S. G. Cmcm; a = 3.8634(2) Å, b = 29.4808(2) Å, c = 7.6945(5) Å) were confirmed respectively using the Rietveld and Le Bail methods utilizing the powder X-ray diffraction data. The n = 4 members, KPrNa2Nb4O13 and KPrCa2Nb2Ti2O13 are synthesized through high-temperature ceramic methods. The compounds are phase pure as confirmed from the X-ray diffraction data and were characterized by UV–visible diffuse reflectance measurements. These two-dimensional oxides also undergo facile topochemical ion-exchange and intercalation reactions and opens up several interesting possibilities. We have replaced the K+ ions in the interlayer by H+, Li+, Na+ ions and [CuCl]+ groups through low temperature reactions. The usefulness of various Dion-Jacobson layered perovskite oxides for potential photocatalytic applications has been explored by determining the optical band gaps, the valence band, and the conduction band energy levels based on the UV–visible diffuse reflectance measurements.

Modified 3ω conductivity technique for measurements of thermal conductivity in cryogenic fluids

An instrument based on a modification to the 3-omega thermal conductivity technique that allows precise measurement of thermal properties in fluids is presented. Existing hot-wire techniques have difficulty measuring thermal conductivity because of the effects of natural convection distorting the measurement, however the standard 3-omega technique has been used extensively in the measurement of the properties of solids with great success. To address the challenge posed by natural convection in fluids, we modify the boundary condition of the 3-omega device configuration to be finite in extent, thereby restricting fluid motion and enabling a direct high-precision measurement of a fluid’s thermal conductivity. This modified scenario also presents an opportunity for a simultaneous measurement of the thermal diffusivity of the fluid. The behavior of the device is described with the reformed boundary conditions to show how a simultaneous measurement is made. By applying a constant temperature finite boundary condition, the solution characteristic in the frequency domain gains features that allow for simultaneous measurements of the fluid thermal conductivity and diffusivity. Given the density of the fluid, measured separately, the specific heat of the fluid can be calculated. The effects of the thermal properties of the measurement wire influence the measurement characteristic, and only when the wire thermal properties are sufficiently small compared to those of the fluid can a simultaneous measurement be made. Due to limitations in the dynamic reserve of the measurement devices, a setup is described that allows the signal of interest to be extracted and a precise measurement to be made with minimal distortion. Initial data on the thermal conductivity of helium is presented in the 4-300K temperature range. Preliminary specific heat data is also presented. Limitations on the device’s thermal properties prevent a specific heat measurement above 70K. This data is compared with reference fluid properties databases to validate the device performance.

Detecting clear‐sky periods from photovoltaic power measurements

AbstractA method for detecting clear‐sky periods from photovoltaic (PV) power measurements is presented and validated. It uses five tests dealing with parameters characterizing the connections between the measured PV power and the corresponding clear‐sky power. To estimate clear‐sky PV power, a PV model has been designed using as inputs downwelling shortwave irradiance and its direct and diffuse components received at ground level under clear‐sky conditions as well as reflectivity of the Earth's surface and extraterrestrial irradiance, altogether provided by the McClear service. In addition to McClear products, the PV model requires wind speed and temperature as inputs taken from ECMWF twentieth century reanalysis ERA5 products. The performance of the proposed method has been assessed and validated by visual inspection and compared to two well‐known algorithms identifying clear‐sky periods with broadband global and diffuse irradiance measurements on a horizontal surface. The assessment was carried out at two stations located in Finland offering collocated 1‐min PV power and broadband irradiance measurements. Overall, total agreement ranges between 84% and 97% (depending on the season) in discriminating clear‐sky and cloudy periods with respect to the two well‐known algorithms serving as reference. The disagreement fluctuating between 6% and 15%, depending on the season, primarily occurs while the PV module temperature is adequately high and/or when the sun is close to the horizon with many more interactions between the radiation, the atmosphere and the ground surface.

Characterization of Mixing at the Edge of a Kuroshio Intrusion into the South China Sea: Analysis of Thermal Variance Diffusivity Measurements

Abstract The Kuroshio occasionally carries warm and salty North Pacific Water into fresher waters of the South China Sea, forming a front with a complex temperature–salinity (T–S) structure to the west of the Luzon Strait. In this study, we examine the T–S interleavings formed by alternating layers of North Pacific Water with South China Sea Water in a front formed during the winter monsoon season of 2014. Using observations from a glider array following a free-floating wave-powered vertical profiling float to calculate the fine-scale parameters Turner angle, Tu, and Richardson number, Ri, we identified areas favorable to double-diffusion convection and shear instability observed in a T–S interleaving. We evaluated the contribution of double-diffusion convection and shear instabilities to the thermal variance diffusivity, χ, using microstructure data and compared it with previous parameterization schemes based on fine-scale properties. We discover that turbulent mixing is not accurately parameterized when both Tu and Ri are within critical ranges (Tu &gt; 60; Ri &lt; ¼). In particular, χ associated with salt finger processes was an order of magnitude higher (6.7 × 10−7 K2 s−1) than in regions where only velocity shear was likely to drive mixing (8.7 × 10−8 K2 s−1).

Deep learning neural network approach to thermal-wave imaging of damage in solids with application to diffusivity measurements of a green (unsintered) metal powder compact slab

A method is proposed to measure the thermal diffusivity of a green (unsintered) metal powder compact slab by combining numerical solution and deep learning. The thermal diffusion and thermal-wave equation is first discretized in space and time domains. Square wave excitation signals at different frequencies are considered, and the corresponding thermal wave responses are obtained. The space and frequency dependencies of the thermal-wave amplitude and phase are obtained by using lock-in thermography. Then, deep learning candidate neural network sets composed of spatial coordinates, excitation frequency, amplitude, and phase values are quickly and massively obtained for training the deep learning network. The validity of the deep learning network is verified by predicting the known thermal diffusivity, and the parameters and robustness of the deep learning network are discussed. Experimentally, a square wave modulated laser beam is used to illuminate one side of a green metal powder compact slab and the spatial distribution of amplitude and phase at three excitation frequencies is obtained. The predicted slab thermal diffusivity is extracted through the formed deep learning network, and the validity of the predicted value is verified by comparing with independent measurements.