Spatial Deviation Research Articles

SAR Ship Image Speckle Noise Suppression Algorithm Based on Adaptive Bilateral Filter

Aiming at the shortcomings of traditional bilateral filtering in suppressing speckle noise in SAR ship images, especially strong speckle noise and loss of image edge details, it proposes an improved bilateral filtering algorithm based on fast adaptive threshold and variable window in this paper. The algorithm was used to suppress speckle noise in SAR ship images. The traditional bilateral filtering cannot effectively filter out the strong speckle noise, but the SAR image has strong speckle noise because of the defects of its imaging principle. To solve these problems, an image sample truncation method based on fast adaptive truncation statistical characteristics is designed to adjust the photometric similarity weight characteristics to realize the adaptive adjustment of spatial standard deviation and gray standard deviation. After the local reference window is modified and truncated according to the local characteristics of the image, the adjusted combined similarity weight value greatly reduces the impact of strong speckle noise on the image. It is smoothed into speckle signal with strong impulse noise. In the traditional bilateral filtering, in order to enhance the effect of smoothing noise, it is necessary to specify a large value of geometric diffusion factor and gray similarity diffusion factor, resulting in the loss of image details. Based on the variable window size filtering method, when the extended local reference window is in the case of nonuniform edge, its window can be enlarged to make the speckle noise stronger. When an extended window contains details such as edges and textures, its size is not expanded to maintain image detail. This method can further smooth the speckle noise in the uniform region while preserving the edge details of the image. Finally, the adaptive truncated sample is used as the input of the bilateral filter. The image sample truncation method based on fast adaptive threshold can effectively eliminate the strong speckle noise information that affects the photometric similarity and weight accuracy of the image. The method based on variable window can greatly enhance the smoothness of the edge area of the image. The experimental results show that improved adaptive bilateral filtering algorithm improves the speckle noise removal ability by 16.06% compared with the traditional bilateral filtering algorithm in the speckle noise suppression of the SAR ship image, and the preservation performance of the image edge after filtering is improved by 5.41%. Compared with the original image, the filtered image has a 1.2% improvement in structural similarity. The algorithm can effectively suppress speckle noise and has a good ability to retain edge and texture information of the SAR ship image, which has strong practicability.

Iterative Learning Control for Precise Aircraft Trajectory Tracking in Continuous Climb and Descent Operations

This paper presents an iterative learning control method for precise aircraft trajectory tracking. Given a trajectory to be followed by an aircraft with a dynamical model which is assumed to be known, the proposed algorithm improves the system performance in following the trajectory using the spatial and temporal deviations suffered by previous flights to anticipate recurring disturbances and compensate for them proactively by generating a new reference trajectory to be followed, which is the input for the aircraft’s own trajectory tracking controller. The proposed method is tested in a simulated busy terminal maneuvering area in which the time-based separation between aircraft is short enough for similar weather conditions to be expected. The numerical experiments are conducted considering aircraft of the same type, which are assumed to follow the same trajectory in two operations in which precise trajectory tracking is essential: continuous climb and descent operations. The obtained results show a significant reduction of the trajectory tracking error in few iterations, proving the effectiveness of the iterative learning control method applied to commercial aircraft trajectory tracking. Higher precision in trajectory tracking implies higher predictability of aircraft trajectories, which results in an improvement of the efficiency and capacity of the air traffic management system and in reductions of costs and emissions.

Spatial uncertainty in herbarium data: simulated displacement but not error distance alters estimates of phenological sensitivity to climate in a widespread California wildflower

Herbarium records provide a broad spatial and temporal range with which to investigate plant responses to environmental change. Research on plant phenology and its sensitivity to climate has advanced with the increasing availability of digitized herbarium specimens, but limitations of specimen‐derived data can undermine the inferences derived from such research. One issue that has received little attention is collection site uncertainty (i.e. error distance), a measure of confidence in the location from which a specimen was collected. We conducted comparative analyses of phenoclimatic models to determine whether spatial deviations of 2, 5, 15 or 25 km between recorded and simulated collection sites, as well as the error distance reported in digitized records, affect estimates of the phenological sensitivity of flowering time to annual temperature and precipitation in a widespread annual California wildflower. In this approach, we considered both spatial and interannual variation in climatic conditions. Simulated site displacements led to increasingly weak estimates of phenological sensitivity to temperature and precipitation anomalies with increasing distances. However, we found no significant effect of reported error distance magnitude on estimates of phenological sensitivity to climate normals or anomalies. These findings suggest that the spatial uncertainty of collection sites among specimens of widely collected plant species may not adversely affect estimates of phenological sensitivity to climate, even though real discrepancies and georeferencing inaccuracy can negatively impact such estimates. Collection site uncertainty merits further attention as a potential source of noise in herbarium data, especially for research on how plant traits respond to spatial and interannual climatic variation.

Spatial Variations of pH in Electrodialysis Stacks: Theory

Electrodialysis (ED) is a well-known electrochemical water desalination technology investigated since the 1950s. In an ED stack, desalination is driven by an applied voltage, which results in selective salt ion electromigration through alternating cation and anion exchange membranes. Transport of hydronium and hydroxide ions during water treatment, together with water dissociation, can lead to unfavorable product acidity or alkalinity, compromise the membrane charge, or enhance scaling. Conversely, pH deviations can also be leveraged to tune the speciation of weak acid/base electrolytes to enhance chlorine disinfectant efficiency, or facilitate electrostatic removal of contaminants with pH-dependent properties. Thus, it is important to understand the effect of varying feedwater salinity and other system parameters on spatial pH deviations in the vicinity of the membrane, and on the pH of the product water.In this work, we extend ED theory to include pH effects in a repeating unit operated in the underlimiting current regime. Different from the single ion exchange membrane repeating unit considered by Sonin and Probstein [1], which is not applicable for systems including pH effects, we solve the concentration profiles of both the salt and water ions in a full repeating unit comprised of a cation exchange membrane and anion exchange membrane pair. To the first time to our knowledge, our model domain encompasses the entire ED repeating unit without assuming prescribed stagnant layer thickness in which the water dissociation reaction occurs. We solve the Nernst-Planck and electroneutrality set of equations in the channels and non-ideal IEMs, following the approach utilized for capturing pH effects in membrane capacitive deionization [2,3] and reverse osmosis [4,5]. We presented results showing fundamental features, including the concentration and pH distribution in the diluate channel, local flux density across the IEMs, and effluent salinity and pH. Our model predicts that including or excluding pH effects lead to essentially identical predictions for salt fluxes across the IEMs, and thus previous models neglecting pH effects are likely accurately predicting desalination. We also show that reducing salinity augments pH perturbations, but that the effluent pH, which consists of mixed acid and alkaline boundary layers at the diluate channel outlet, does not deviate from inlet neutral pH significantly. In the future, this model framework here can be extended to include multi-ionic solution and species with pH-dependent properties, and validated with a dedicated set of experimental results.

Characterizing the spatiotemporal dynamics of shallow soil water stable isotopic compositions on a karst hillslope in Southwestern China

• Soil water stable isotopic compositions (SWSIC) exhibited large spatiotemporal variations. • SWSIC showed less temporal stability than soil water content (SWC). • SWSIC variations were less explained by environmental controls compared to SWC variations. • Temporal stability analysis method can be used to select representative sites for SWSIC. Knowledge of the spatiotemporal dynamics of soil water content (SWC) and soil water stable isotopic compositions (SWSIC) is critical for understanding water exchanges across the atmosphere-land interface. However, compared with those of SWC, studies on the spatiotemporal characteristics of SWSIC are still scarce, which limits their use for more accurately characterizing terrestrial ecohydrological processes. To examine whether SWSIC and SWC share similar spatiotemporal features, their spatiotemporal patterns along with relevant controls were investigated at shallow soils (0–10 cm) on a karst hillslope in Southwest China, based on seven sampling campaigns conducted over a two-year period. The results revealed considerable spatiotemporal variations in SWSIC. Compared to SWC, δD values exhibited smaller spatial variations, while line-conditioned excess (lc-excess) values exhibited considerably larger ones, suggesting that soil evaporation heterogeneity might not be the primary reason for spatial variations in δD of soil water in this study. The spatial structures of SWSIC were less temporally stable than those of SWC due to the combined impact of land surface processes and temporal variations in isotopic compositions of input water on SWSIC. Moreover, the spatiotemporal patterns of SWSIC were less explained by environmental variables that were also differed from those of SWC, suggesting that the knowledge gained from SWC studies might not be directly transferable to understand SWSIC spatiotemporal characteristics. Nevertheless, it should be highlighted that the temporal stability analysis method initially proposed for studying SWC could be extended to select representative sites for monitoring areal average SWSIC, due to the temporal persistence of the SWSIC spatial structures. In addition, a negative correlation between the spatial mean and standard deviation of lc-excess was found, indicating that the associated spatial variability increased with areal mean kinetic fractionation signals caused by soil evaporation. These findings have important implications for designing SWSIC monitoring schemes, which in turn can improve the interpretation of SWSIC data for various application purposes.

Increasing Inhomogeneity of the Global Oceans

AbstractThe ocean is inhomogeneous in hydrographic properties with diverse water masses. Yet, how this inhomogeneity has evolved in a rapidly changing climate has not been investigated. Using multiple observational and reanalysis datasets, we show that the spatial standard deviation (SSD) of the global ocean has increased by 1.4 ± 0.1% in temperature and 1.5 ± 0.1% in salinity since 1960. A newly defined thermohaline inhomogeneity index, a holistic measure of both temperature and salinity changes, has increased by 2.4 ± 0.1%. Climate model simulations suggest that the observed ocean inhomogeneity increase is dominated by anthropogenic forcing and projected to accelerate by 200%–300% during 2015–2100. Geographically, the rapid upper‐ocean warming at mid‐to‐low latitudes dominates the temperature inhomogeneity increase, while the increasing salinity inhomogeneity is mainly due to the amplified salinity contrast between the subtropical and subpolar latitudes.

Influence of Commercial-Scale Seaweed Cultivation on Water Quality: A Case Study in a Typical Laver Culture Area of the Yellow Sea, North China

Seaweeds are important to marine ecosystems through biogeochemical processes. Laver are the most widely farmed seaweeds with the largest culture area in China. This study analyzes the water quality characteristics in a large-scale laver culture area (Taoluo) by comparing a small-scale laver culture area and non-culture areas, thereby assessing the changes in water quality due to large-scale laver cultivation. Particulate organic carbon and/or dissolved organic carbon decreased while the total suspended solid increased seasonally or with the distance from the coast. The concentrations of total nitrogen as well as dissolved inorganic nitrogen and phosphorus were generally higher near the shore and decreased seasonally in Taoluo. Substantial spatial variation in nutrient parameters between culture and non-culture sites was observed. Moreover, significant variations between culture and non-culture sites on a spatio-temporal scale were mostly observed in December compared with September and October. Furthermore, more clusters were found in December based on the water quality characteristics in various sampling sites using a hierarchical clustering analysis. These results suggested that more spatial deviation in water quality parameters between culture and non-culture sites were found in December; thus it can be hypothesized that the changes in water quality due to large-scale cultivation for laver was likely to occur in northern China in winter, i.e., the period of best growth status for the cold-temperate species of laver (e.g., Neopyropia yezoensis). We hope that this study can help to further understand the effects of seaweed farming on marine environments.

Extraction of Electromechanical Coefficients from Capacitance–Voltage Measurements of Unannealed Solution‐Processed KNN Thin Films: Effects of Frequency and Electrostatic and Mechanical Deformation

A solution‐processed piezoceramic thin‐film MπM parallel‐plate capacitor structure to determine electromechanical coefficient using capacitance–voltage measurements is demonstrated. Electrical loading is applied to the capacitor to stimulate out‐of‐plane longitudinal and transverse elongation. The piezoelectric coefficient (d 33) is estimated using the spatial deviation of thin‐film dimensions as a function of the applied electric field. The results are validated using finite element method‐based modeling and compared with several measurements in literature, including piezoresponse force microscopy‐based measurements, which are generally considered unreliable due to strong electrostatic interactions between the tip‐cantilever, and the charged sample surface, wherein such artifacts result in the overestimation of the electromechanical response of the material under investigation.

Driving Simulator Trajectory-Level Analysis of Truck Drivers’ Behavioral Alteration in Connected Vehicles Environment Under Fog with Complex Roadway Geometry

Foggy weather increases crash likelihood when coinciding with roadway geometry changes inconsistent with drivers’ expectations. The situation might be exacerbated for heavy trucks having to evade critical safety events because of the vehicles’ maneuverability limitations, imposing prime safety challenges on major freight corridors like Interstate-80 (I-80) in the U.S. Aligned with the connected vehicle (CV) pilot program on I-80 in Wyoming, this study intends to unveil how CV technology alleviates safety concerns in this regard. To this aim, a with/without analysis approach was performed utilizing a high-fidelity truck driving simulator. Twenty-three professional truck drivers were recruited to drive the simulator in CV scenario with traveler information messages, including foggy weather ahead and an advisory speed of 45 mph, and in a non-CV counterpart without notifications. Longitudinal and lateral drivers’ behaviors were quantified by kinematic-based surrogate measures of safety (K-SMoS) characterized on vehicles’ trajectory, including longitudinal speed, lateral speed, steering, their corresponding spatial standard deviations, and the coefficient of variation of longitudinal speed. The central tendency and dispersion of K-SMoS distributions were compared between CVs and non-CVs throughout the simulated roadway. Results showed immediate truck drivers’ compliance to CV notifications, which was more apparent in their longitudinal driving behaviors. On a horizontal curve with poor visibility, statistically significant reductions in central tendency and dispersion of K-SMoS distributions up to 67% in CVs were observed, minimizing the crash risk in CV environments. Besides, findings revealed that exposure to the CV notifications minimized drivers’ behavior uncertainty, manifesting in their improved situational awareness and enhancing the safety performance of the traffic stream.

The hydrostatic control of load-induced height changes above subglacial Lake Vostok

Abstract Lake Vostok, East Antarctica, represents an extensive water surface at the base of the ice sheet. Snow, ice and atmospheric pressure loads applied anywhere within the lake area produce a hydrostatic response, involving deformations of the ice surface, ice–water interface and particle horizons. A modelling scheme is developed to derive height changes of these surfaces for a given load pattern. It is applied to a series of load scenarios, and predictions based on load fields derived from a regional climate model are compared to observational datasets. Our results show that surface height changes due to snow-buildup anomalies are damped over the lake area, reducing the spatial standard deviation by one-third. The response to air pressure variations, in turn, adds surface height variability. Atmospheric pressure loads may produce height changes of up to $\pm$ 4 cm at daily resolution, but decay rapidly with integration time. The hydrostatic load response has no significant impact neither on ICESat laser campaign biases determined over the lake area nor on vertical particle movements derived from GNSS observations.

Investigating the sense of agency and its relation to subclinical traits using a novel task

Tasks measuring the sense of agency often manipulate the predictability of action outcomes by introducing spatial deviation. However, the extent to which spatial predictability of an outcome influences the sense of agency when spatial deviation is controlled for remains untested. We used a novel task to investigate the effect of several factors (action–outcome contingency, spatial deviation, and spatial predictability when controlling for spatial deviation of action outcomes) on the sense of agency. We also investigated trait predictors of metacognition of agency—the degree to which participants’ confidence in their agency judgements corresponds to the accuracy of those judgements. Initial and replication samples completed contingency, deviation, and predictability versions of the task. Across samples, participants’ sense of agency was impacted by action–outcome contingency and spatial deviation of action outcomes. Manipulation of the spatial predictability of action outcomes did not reliably impact the sense of agency. Metacognition of agency was related to alexithymic traits—higher alexithymia scores were associated with reduced metacognition of agency.

Towards an objective evaluation of EEG/MEG source estimation methods – The linear approach

The spatial resolution of EEG/MEG source estimates, often described in terms of source leakage in the context of the inverse problem, poses constraints on the inferences that can be drawn from EEG/MEG source estimation results. Software packages for EEG/MEG data analysis offer a large choice of source estimation methods but few tools to experimental researchers for methods evaluation and comparison. Here, we describe a framework and tools for objective and intuitive resolution analysis of EEG/MEG source estimation based on linear systems analysis, and apply those to the most widely used distributed source estimation methods such as L2-minimum-norm estimation (L2-MNE) and linearly constrained minimum variance (LCMV) beamformers. Within this framework it is possible to define resolution metrics that define meaningful aspects of source estimation results (such as localization accuracy in terms of peak localization error, PLE, and spatial extent in terms of spatial deviation, SD) that are relevant to the task at hand and can easily be visualized. At the core of this framework is the resolution matrix, which describes the potential leakage from and into point sources (point-spread and cross-talk functions, or PSFs and CTFs, respectively). Importantly, for linear methods these functions allow generalizations to multiple sources or complex source distributions. This paper provides a tutorial-style introduction into linear EEG/MEG source estimation and resolution analysis aimed at experimental (rather than methods-oriented) researchers. We used this framework to demonstrate how L2-MNE-type as well as LCMV beamforming methods can be evaluated in practice using software tools that have only recently become available for routine use. Our novel methods comparison includes PLE and SD for a larger number of methods than in similar previous studies, such as unweighted, depth-weighted and normalized L2-MNE methods (including dSPM, sLORETA, eLORETA) and two LCMV beamformers. The results demonstrate that some methods can achieve low and even zero PLE for PSFs. However, their SD as well as both PLE and SD for CTFs are far less optimal for all methods, in particular for deep cortical areas. We hope that our paper will encourage EEG/MEG researchers to apply this approach to their own tasks at hand.

Bifurcations of Solutions to Equations with Deviating Spatial Arguments

A periodic boundary-value problem for an equation with deviating spatial argument is considered. This equation describes the phase of a light wave in light resonators with distributed feedback. Optical systems of this type are used in computer technologies and in the study of laser beams. The boundary-value problem was considered for two values of spatial deviations. In the work, bifurcation problems of codimensions 1 and 2 were analyzed by various methods of studying dynamical systems, for example, the method of normal Poincaré–Dulac forms, the method of integral manifolds, and asymptotic formulas. The problem on the stability of certain homogeneous equilibrium states is examined. Asymptotic formulas for spatially inhomogeneous solutions and conditions for their stability are obtained.

Two-dimensional mapping of the ultrasonic attenuation and speed of sound in brain

Brain is inhomogeneous due to its composition of different tissue types (gray and white matter), anatomical structures (e.g. thalamus and cerebellum), and cavities in the brain (ventricles). These inhomogeneities lead to spatial variations in the ultrasonic properties of the organ. The goal of this study is to characterize the spatial variation of the speed of ultrasound and frequency slope of attenuation in fixed sheep brain. 1-cm-thick slices of tissue from the coronal, sagittal and transverse cardinal planes were prepared from 12 brains. Ultrasonic measurements were performed using broadband transducers with center frequencies of 3.5, 5.0, 7.5 and 10 MHz. By mechanically scanning the transducers over the specimens, two-dimensional maps of the speed of sound (SOS) and frequency slope of attenuation (FSA) were produced. Measured values for the spatial mean and standard deviation of FSA ranged between 0.59 and 0.81 dB/cm·MHz and 0.29–0.60 dB/cm·MHz, respectively, depending on the specimen and transducer frequency. Measured values for the spatial mean and standard deviation of SOS ranged from 1532–1541 m/s and 10–14 m/s, respectively. Detailed, two-dimensional maps of FSA and SOS were produced, representing the first such characterization of the spatial variation of the ultrasonic properties of normal mammalian brain.

The Namib Turbulence Experiment: Investigating Surface–Atmosphere Heat Transfer in Three Dimensions

Abstract The Namib Turbulence Experiment (NamTEX) was a multinational micrometeorological campaign conducted in the central Namib Desert to investigate three-dimensional surface layer turbulence and the spatiotemporal patterns of heat transfer between the subsurface, surface, and atmosphere. The Namib provides an ideal location for fundamental research that revisits some key assumptions in micrometeorology that are implicitly included in the parameterizations describing energy exchange in weather forecasting and climate models: homogenous flat surfaces, no vegetation, little moisture, and cloud-free skies create a strong and consistent diurnal forcing, resulting in a wide range of atmospheric stabilities. A novel combination of instruments was used to simultaneously measure variables and processes relevant to heat transfer: a 3-km fiber-optic distributed temperature sensor (DTS) was suspended in a pseudo-three-dimensional array within a 300 m × 300 m domain to provide vertical cross sections of air temperature fluctuations. Aerial and ground-based thermal imagers recorded high-resolution surface temperature fluctuations within the domain and revealed the spatial thermal imprint of atmospheric structures responsible for heat exchange. High-resolution soil temperature and moisture profiles together with heat flux plates provided information on near-surface soil dynamics. Turbulent heat exchange was measured with a vertical array of five eddy-covariance point measurements on a 21-m mast, as well as by collocated small- and large-aperture scintillometers. This contribution first details the scientific goals and experimental setup of the NamTEX campaign. Then, using a typical day, we demonstrate (i) the coupling of surface layer, surface, and soil temperatures using high-frequency temperature measurements, (ii) differences in spatial and temporal standard deviations of the horizontal temperature field using spatially distributed measurements, and (iii) horizontal anisotropy of the turbulent temperature field.

Spatial variations of pH in electrodialysis stacks: Theory

Electrodialysis (ED) is a well-known electrochemical water desalination technology investigated since the 1950s. In an ED stack, desalination is driven by an applied voltage, which results in selective salt ion electromigration through alternating cation and anion exchange membranes. Transport of hydronium and hydroxide ions during water treatment, together with water dissociation, can lead to unfavorable product acidity or alkalinity, compromise the membrane charge, or enhance scaling. Conversely, pH deviations can also be leveraged to tune the speciation of weak acid/base electrolytes to enhance chlorine disinfectant efficiency, or facilitate electrostatic removal of contaminants with pH-dependent properties. Thus, it is important to understand the effect of varying feedwater salinity and other system parameters on spatial pH deviations in the vicinity of the membrane, and on the pH of the product water. In this work, we propose an ED model including pH effects in a repeating unit operated in the underlimiting current regime. We numerically solve the concentration profiles of both the salt and water ions in a full repeating unit comprised of a cation and anion exchange membrane pair. For the first time to our knowledge, our model domain encompasses the entire ED repeating unit without assuming prescribed stagnant layer thickness in which the water dissociation reaction occurs. This model can be utilized to compare to experimental datasets in the future, and provide insight towards designing ED systems for removal of pH-dependent species.

A Comprehensive Approach for Measuring Spatial Deviations of Computer-Assisted Mandibular Reconstruction.

Computer-assisted surgery has become the mainstream in mandibular reconstruction, but the lack of a standard measuring approach for spatial deviations of mandible hinders postoperative verification and the comparison of different subjects. This study aims to set up a comprehensive approach for measuring spatial deviations of computer-assisted mandibular reconstruction. A systematic review was conducted to extract all measurements for computer-assisted mandibular reconstruction. Thereafter, eligible measurements were included in the authors' comprehensive approach, which categorized the measurements according to different anatomical structures and landmarks. A total of 80 studies were included in the authors' systematic review, and 31 measurements were extracted. The authors established a comprehensive panel of anatomical landmarks to facilitate measurement, including parts, points, lines, planes, and angles. These measurements encompassed spatial deviations of the overall mandible, condyle, gonial angle, bone grafts, midline, surgical plate, osteotomy, and miscellaneous indicators. A calculation spreadsheet was developed to collect landmarks and compute deviations automatically with built-in formulas. Finally, a simplified panel of measurements was recommended for spatial deviations of mandibular reconstruction. A comprehensive approach for measuring spatial deviations of computer-assisted mandibular reconstruction was established. Future studies will confirm this approach as an effective and scientific system for postoperative verification of computer-assisted mandibular reconstruction.

A global 1‐km downscaled SMAP soil moisture product based on thermal inertia theory

AbstractMicrowave remote sensing technology has been applied to produce soil moisture (SM) retrievals on a global scale for various studies and applications. However, due to the limitations of current technology, the native spatial resolution of currently available passive microwave SM products is on the order of tens of kilometers, and this resolution cannot be used to characterize SM variability on a regional scale. To overcome this limitation, a downscaling algorithm based on the thermal inertia theory–derived relationship between SM and temperature difference was developed using outputs from the Global Land Data Assimilation System–Noah Land Surface Model and the land long‐term data record–Advanced Very High Resolution Radiometer normalized difference vegetation index (NDVI) dataset and applied to the Aqua Moderate Resolution Imaging Spectroradiometer land surface temperature/NDVI data to produce a downscaled 1‐km Soil Moisture Active Passive (SMAP) radiometer daily SM product, respectively, at 6:00 a.m. and 6:00 p.m. on a global scale from 2015 to 2020. The evaluation results reveal that the downscaling model performs better in the middle or low latitudes than in high latitudes. It also performs better in warm months than in cold months. The in situ SM observations from dense networks around the world were used to validate the 1‐km and enhanced 9‐km SMAP SM data. The validation metrics indicated that both the 1‐km and 9‐km SM data have overall overestimation trends, and the unbiased RMSE (0.063 m3m–3on average), mean absolute error (0.052 m3m–3on average), and spatial standard deviation (0.025 m3m–3on average) of the 1 km data are generally more accurate than the metrics of the 9‐km SM data, which indicates that the downscaled data provide reliable observed SM information.

A flow-diffusion model of oxygen transport for quantitative mapping of cerebral metabolic rate of oxygen (CMRO2) with single gas calibrated fMRI

One promising approach for mapping CMRO2 is dual-calibrated functional MRI (dc-fMRI). This method exploits the Fick Principle to combine estimates of CBF from ASL, and OEF derived from BOLD-ASL measurements during arterial O2 and CO2 modulations. Multiple gas modulations are required to decouple OEF and deoxyhemoglobin-sensitive blood volume. We propose an alternative single gas calibrated fMRI framework, integrating a model of oxygen transport, that links blood volume and CBF to OEF and creates a mapping between the maximum BOLD signal, CBF and OEF (and CMRO2). Simulations demonstrated the method’s viability within physiological ranges of mitochondrial oxygen pressure, PmO2, and mean capillary transit time. A dc-fMRI experiment, performed on 20 healthy subjects using O2 and CO2 challenges, was used to validate the approach. The validation conveyed expected estimates of model parameters (e.g., low PmO2), with spatially uniform OEF maps (grey matter, GM, OEF spatial standard deviation ≈ 0.13). GM OEF estimates obtained with hypercapnia calibrated fMRI correlated with dc-fMRI (r = 0.65, p = 2·10−3). For 12 subjects, OEF measured with dc-fMRI and the single gas calibration method were correlated with whole-brain OEF derived from phase measures in the superior sagittal sinus (r = 0.58, p = 0.048; r = 0.64, p = 0.025 respectively). Simplified calibrated fMRI using hypercapnia holds promise for clinical application.

Sensorimotor adaptation in VR: magnitude and persistence of the aftereffect increase with the number of interactions

In both prism and virtual reality experiments, it has been observed that visual displacement leads to an adaptation of the sensorimotor system. A characteristic of adaptation is the occurrence of the aftereffect, which is the spatial deviation of the movements in the direction opposite to the visual displacement. Prism adaptation experiments have shown that a higher number of interactions lead to an increased magnitude and persistence of the aftereffect. The aim of the present study was to investigate this relationship in virtual reality. After baseline measurement, the virtual environment was displaced visually. During this adaptation phase, the participants performed either zero, five, or thirty-five pointing movements. Afterwards, all participants performed the pointing movements without the visual displacement in the virtual environment. Performing five pointing movements during the adaptation phase was already sufficient to produce an aftereffect. With thirty-five pointing movements, both magnitude and persistence of the aftereffect increased. These results replicate studies of prism adaptation. Considering this, we briefly discuss the suitability of virtual reality as a research tool to study prism adaptation.