Vertical Bias Research Articles

Process-based evaluation of intraseasonal oceanic Kelvin waves in the Pacific Ocean in CMIP6 models

Abstract Oceanic intraseasonal Kelvin waves (KWs) help modulate upper-ocean thermal characteristics, providing feedbacks to important coupled air-sea phenomena in the tropics. The recent availability of daily thermocline depth fields from several CMIP6 models makes it possible to evaluate the performance of KWs and identify potential sources of bias. Most models fail to simulate a realistic spatial distribution of KW variability. Models simulate large variability of KWs in the western or eastern Pacific rather than in the central Pacific as observed. The modeled KWs propagate slowly (about 1.5 m/s) compared to observations (about 2.5 m/s). This slow propagation is also identified in wavenumber-frequency spectra for KWs and meridional KW structures, which is more consistent with a second baroclinic mode structure in models compared to the first baroclinic mode structure in observations. An analysis of the relative contributions of vertical wavenumber and background ocean stability to KW phase speeds indicates that the high vertical wavenumber bias in models contributes most to the slow propagation, in which the higher-than-observed vertical wavenumbers implying the biased incorporation of higher baroclinic modes in model KW structure. This finding is further supported by the results of vertical mode decomposition that incorporates background density profiles. These results indicate that a realistic representation of the KW vertical structure is essential to produce realistic KW propagations in models.

Exchange bias and topological Hall effect of Fe and Co intercalated NbS2 single crystals

In recent years, the topological Hall effect generated by noncoplanar magnetic structures has been studied extensively. Some two-dimensional chalcogenides with 3d transition metal intercalations also exhibit similar properties. In this study, we investigated the crystalline structure and the magnetic and transport properties of Fe and Co codoped NbS2 single crystals. The structural results indicate disorder between the Fe and Co atoms within the interlayers of NbS2. Magnetic measurements showed that the vertical exchange bias effect appeared below the Néel temperature (TN), with a maximum value of approximately 2.5 mμB/f.u. at 2 K, which can be ascribed to the appearance of a spin-glass state. Additionally, accompanying the antiferromagnetic phase transition, nontrivial electrical transport properties were observed. Below TN, the magnetoresistance became positive and exhibited an initial increase, followed by a decrease with decreasing temperature. The Hall resistivity shows a hump-like curve near TN, indicating a topological Hall effect. This behavior is related to fluctuations in the spin chirality, which affects the scattering of charge carriers. Based on the correlation between the magnetoresistance and Hall resistivity responses, it is believed that the magnetic moments of the doped Fe and Co atoms in a single crystal compete with each other near the Néel temperature, resulting in complex magnetic structures such as noncoplanar and noncollinear arrangements. Such a two-dimensional antiferromagnetic material system provides an ideal platform for studying unconventional transport mechanisms.

Decadal-scale assessment of sediment denudation rates in the Zhoukou River Basin, Taiwan: insights from improved DEMs of differencing based on spectral analysis

This study assesses sediment erosion rates in the Zhoukou River Basin in southern Taiwan over the past three decades, focusing on the impact of extreme rainfall events. While various established methods determine erosion rates over different temporal scales, we employ an independent approach for decadal-scale erosion rate calculation by utilizing open-source global and regional digital elevation models (DEMs) data for two distinct periods. We introduce a new method that applies Fourier analysis to vertically register the DEMs, significantly minimizing their vertical bias. Through spectral analysis, we identify long wavelength topography crucial for correcting vertical offsets. Erosion rates, computed through DEMs of Difference (DoD), exhibit a similar trend of significant reduction in sediment export rates from 1990–2010 to 2011–2020 due to decreased extreme rainfall events, aligning with erosion rate estimates derived from mean suspended load data at gauge stations. Over the entire period from 1990 to 2020, the calculated denudation rate was 14.19 mm/yr, whereas in the recent decade (2011–2020), it decreased to 10.46 mm/yr. Our study suggests that the improved DoD method can effectively estimate sediment transport rates by leveraging underutilized DEMs captured at distinct points in time, especially when the erosional signal dominates data noise.

Measurement Biases in Ocean Temperature Profiles from Marine Mammal Dataloggers

Abstract The study focuses on biases in ocean temperature profiles obtained by means of Satellite Relay Data Loggers (SRDL recorders) and time–depth recorder (TDR) attached to marine mammals. Quasi-collocated profiles from Argo floats and from ship-based conductivity–temperature–depth (CTD) profilers are used as reference. SRDL temperature biases depend on the sensor type and vary with depth. For the most numerous group of Valeport 3 (VP3) and conductivity–temperature–fluorescence (CTF) sensors, the bias is negative except for the layer 100–200 m. The vertical bias structure suggests a link to the upper-ocean thermal structure within the upper 200-m layer. Accounting for a time lag which might remain in the postprocessed data reduces the bias variability throughout the water column. Below 200-m depth, the bias remains negative with the overall mean of −0.027° ± 0.07°C. The suggested depth and thermal corrections for biases in SRDL data are within the uncertainty limits declared by the manufacturer. TDR recorders exhibit a different bias pattern, showing the predominantly positive bias of 0.08°–0.14°C below 100 m primarily due to the systematic error in pressure. Significance Statement The purpose of this work is to improve the consistency of the data from the specific instrumentation type used to measure ocean water temperature, namely, the data from miniature temperature sensors attached to marine mammals. As mammals dive during their route to and from their feeding areas, these sensors measure water temperature and dataloggers send the measured temperature data to oceanographic data centers via satellites as soon as the mammals return to the sea surface. We have shown that these data exhibit small systematic instrumental errors and suggested the respective corrections. Taking these corrections into account is important for the assessment of the ocean climate change.

Design of guided wave magnetostrictive patch transducer with vertical static bias magnetic field for pipe inspection

Compared with electromagnetic acoustic transducer (EMAT), magnetostrictive patch transducer (MPT) has higher energy conversion efficiency. MPT is often used to excite and receive long-distance ultrasonic guided waves for defect detection or structural health monitoring of large industrial equipment. In this work, a new design method of permanent magnet MPT using the vertical static bias magnetic field to excite shear horizontal (SH) guided waves is proposed. First, the mathematical model of exciting ultrasonic guided waves by a vertical static bias magnetic field MPT is established, and the equivalent surface stress in the magnetostrictive patch is calculated. It is shown that the vertical static bias magnetic field MPT can excite SH guided waves in plates. Then, the influence of static bias magnetic field intensity on the amplitude of guided wave signal is analyzed. Compared with other traditional MPTs, the amplitude of SH guided wave signal excited by the vertical static bias magnetic field MPT is increased. Finally, a periodic permanent magnet (PPM)-MPT with a central frequency of 120 kHz is designed. The proposed PPM-MPT improves the energy conversion efficiency compared to the circumferential alternating permanent magnet array type MPT. The PPM-MPT can detect defects in a steel pipe with a wall thickness of 3.5 mm and an inner diameter of 100 mm. The results show that the PPM-MPT designed in this paper successfully detects the through hole with a diameter of 2 mm, and the cross-section loss rate of the defect is about 0.6 %.

Tuneable Vertical Hysteresis Loop Shift in Exchange Coupled La0.67Sr0.33MnO3‐SrRuO3 Bilayer

AbstractHarnessing extra degrees of freedom at the heterostructure interface is of crucial importance to bring additional functionalities in modern spintronic devices. Here, a vertical hysteresis loop shift (vertical bias) is demonstrated in an exchange biased system of ferromagnetic thin film heterostructure of La0.67Sr0.33MnO3 (10 nm)‐SrRuO3 (SRO) (20 nm), after field cooling with ±1 T below 100 K close to the Curie temperature (TC) ≈125 K of SRO and loop sweeping under ±1 T field. Besides, a positive exchange bias (HEB) is also observed below TC ≈125 K showing a maximum ≈11 mT at 2 K. The vertical shift is modeled closely using micromagnetic simulations and the layers’ thickness dependency is demonstrated. The reason for the shift is attributed to the simultaneous role of the interfacial antiferromagnetic interaction and the hard anisotropy of SRO against the Zeeman energy. Finally, from the experimental and simulation results, a generalized model of controllable and tunable vertical shift is proposed applicable for other material systems possessing glassy phases, uncompensated/canted spins, absent interfacial exchange coupling, etc., and hence can be informative for the use of vertical shift in future spintronic devices.

Layer-Polarized Anomalous Hall Effects from Inversion-Symmetric Single-Layer Lattices.

In the field of physics and materials science, the discovery of the layer-polarized anomalous Hall effect (LP-AHE) stands as a crucial development. The current research paradigm is rooted in topological or inversion-asymmetric valleytronic systems, making such a phenomenon rather rare. In this work, a universal design principle for achieving the LP-AHE from inversion-symmetric single-layer lattices is proposed. Through tight-binding model analysis, we demonstrate that by stacking into antiferromagnetic van der Waals bilayer lattices, the coupling physics between PT symmetry and vertical external bias can be realized. This coupling reveals the previously neutralized layer-locked Berry curvature, compelling the carriers to move in a specific direction within a given layer, thereby realizing the LP-AHE. Intriguingly, the chirality of the LP-AHE can be effectively switched by modulating the direction of vertical external bias. First-principles calculations validate this mechanism in bilayer T-FeCl2 and MnPSe3. Our results pave the way for new explorations of the LP-AHE.

Enhanced Exchange Bias in Epitaxial High-Entropy Oxide Heterostructures.

High-entropy oxides (HEOs) have gained significant interest in recent years due to their unique structural characteristics and potential to tailor functional properties. However, the electronic structure of the HEOs currently remains vastly unknown. In this work, combining magnetometry measurements, scanning transmission electron microscopy, and element-specific X-ray absorption spectroscopy, the electronic structure and magnetic properties of the perovskite-HEO La(Cr0.2Mn0.2Fe0.2Co0.2Ni0.2)O3 epitaxial thin films are systemically studied. It is found that enhanced magnetic frustration emerges from competing exchange interactions of the five transition-metal cations with energetically favorable half-filled/full-filled electron configurations, resulting in an unprecedented large vertical exchange bias effect in the single-crystalline films. Furthermore, our findings demonstrate that the La(Cr0.2Mn0.2Fe0.2Co0.2Ni0.2)O3 layer with a thickness down to 1 nm can be used as a pinning layer and strongly coupled with a ferromagnetic La0.7Sr0.3MnO3 layer, leading to a notable exchange bias and coercivity enhancement in a cooling field as small as 5 Oe. Our studies not only provide invaluable insight into the electronic structure of HEOs but also pave the way for a new era of large bias materials for spintronics devices.

Altered Perception of the Bistable Motion Quartet in Albinism.

Perception of the motion quartet (MQ) alternates between horizontal and vertical motion, with a bias toward vertical motion. This vertical bias has been explained by the dominance of intrahemispheric processing. In albinism, each hemisphere receives input from both visual hemifields owing to enhanced crossing of the optic nerves at the optic chiasm. This might affect the perception of the ambiguous MQ and particularly the vertical bias. The effect of optic nerve misrouting in persons with albinism and nystagmus (PWA, n = 14) on motion perception for MQ was compared with healthy controls (HC; n = 11) and with persons with nystagmus in the absence of optic nerve misrouting (PWN; n = 12). We varied the ratio of horizontal and vertical distances of MQ dots (aspect ratio [AR]) between 0.75 and 1.25 and compared the percentages of horizontal and vertical motion percepts as a function of AR between groups. For HC, the probability of vertical motion perception increased as a sigmoid function with increasing AR exhibiting the expected vertical percept bias (mean, 58%; median, 54%; vertical motion percepts). PWA showed a surprisingly strong horizontal bias independent of the AR with a mean of 11% (median, 10%) vertical motion percepts. The PWN was in between PWA and HC, with a mean of 34% (median, 47%) vertical perception. Nystagmus alone is unlikely to explain this pattern of results because PWA and PWN had comparable fixation stabilities. The strong horizontal bias observed in PWA and PWN might partly result from the horizontal nystagmus. The even stronger horizontal bias in PWA indicates that the intrahemispherical corepresentation of both visual hemifields may play an additional role. The altered perception of the MQ in PWA opens opportunities to (i) understand the interplay of stability and plasticity in altered visual pathway conditions and (ii) identify visual pathway abnormalities with a perception-based test using the MQ.

Quantification of hydrodynamic model sea level bias utilizing deep learning and synergistic integration of data sources

This study demonstrates the use of machine learning strategies to examine and quantify the bias that often exists in sea level data from hydrodynamic models. The sea level bias is considered to consist of two components: (i) hydrodynamic modelling errors due to numerical modelling limitations, and (ii) a bias related to the difference between vertical datums. The goal is to accurately quantify these components, enabling the determination of absolute dynamic topography from coastal to offshore areas. The method is tested in the Baltic Sea employing a synergy of hydrodynamic models, tide gauges, and satellite altimetry.Firstly, a multivariate deep neural network approach inspired by WaveNet is used to identify and quantify hydrodynamic modelling errors. A wrapper-type sequential feature elimination algorithm identifies seven relevant variables out of the initially considered sixteen for training the deep leaning model in the Baltic Sea region. The model is trained using sixteen tide gauge records. As a result, the model predicts hydrodynamic modelling errors with a root mean squared error of 3.2 cm and 3.4 cm, and an R-Squared value of 0.82 and 0.77 for the training and test sets, respectively. Comparing the predicted and observed errors reveals localized areas where other sea level dynamics, such as seiches in the Gulf of Riga, may be of interest but were not incorporated into the deep learning model. Secondly, once the hydrodynamic modelling errors are quantified, the method allows for the determination of the vertical reference bias by comparing known and reliable observations, such as tide gauge and satellite altimetry data. The vertical reference bias is calculated to be 18.1 ± 2.9 cm.The method significantly improves the accuracy of dynamic topography, resulting in an average root mean squared error of 4.1 cm compared with satellite altimetry and a correlation of 0.98 compared with tide gauges. This approach presents a novel way to integrate modelled and observed dynamic topography using machine learning techniques for enhancing our understanding and its applications.

Enhancing ocean environment prediction in Yellow Sea through targeted observation using ocean acoustic tomography

Ocean Acoustic Tomography (OAT) is an efficient and economical marine acoustic observation technique. Targeted observation is an appealing procedure to reduce the uncertainty of ocean environment prediction through additional observation. This study aimed to assess the validity of OAT as an observation method for targeted observation. OAT based on Niche Genetic Algorithm was employed to extract sound speed and temperature profiles from acoustic transmission time, utilizing data from the 2019 Yellow Sea experiment. The inversion results were compared with measurement data, which are found to be accurate and reliable. To further evaluate OAT as targeted observation method, the vertical bias structure of OAT was added on synchronous measurement data in the sensitive area of targeted observation to simulate OAT observation in sensitive area. This simulated data was then incorporated into a 3D-Var assimilation system to improve the short-term prediction of the target region. Comparing the predictions derived with the measurement data at the verification time, it shows that the simulated OAT observation improved the quality of target region prediction, indicating that OAT can be an effective observation method for targeted observation. An Observing System Simulation Experiment was conducted to assess the impact of OAT characteristics on prediction improvement. The results show that both adding observation nodes and extending the observation duration have positive effects, while extending the observation duration performs better.

Vertical attention bias for tops of objects and bottoms of scenes.

Past research demonstrated a top-salience bias in object identification, with random shapes appearing more similar when they share the same top versus the same bottom. This is consistent with tops of natural objects and lifeforms tending to be more informative locations of intentionality and functionality, leading observers to favor attending to tops. However, this bias may also reflect a generic downward vantage tendency that occurs with more informative interactive aspects of scenes typically lying below the horizon. Two experiments test for this overall pattern of vertical attention bias (VAB) for both objects and scenes. Participants observed picture triptychs and judged if the center object or scene appeared more similar to flanking comparison figures that contain the same top versus same bottom. Experiment 1 used vertically information-balanced impoverished stimuli, either polygon objects or polygon-array scenes. Experiment 2 extended the triptych stimuli to naturalistic objects or scenes. Results generally support a VAB for object tops and scene bottoms that varies as a function of the informative aspects of visually attended stimuli. This pattern held for information-balanced objects but not scenes, however, with more ecologically valid naturalistic stimuli, VAB was large and robust, consistent with a vertical information imbalance that drives a generic downward vantage. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Modeling forest canopy surface retrievals using very high-resolution spaceborne stereogrammetry: (I) methods and comparisons with actual data

The capability of spaceborne stereogrammetry using very high-resolution (VHR, <2 m) imagery with various environmental, experimental, and sensor configurations for characterizing forest canopy surfaces has not been completely explored. Existing archives of VHR imagery include a limited subset of potential stereo image acquisition configurations and may therefore exclude optimal configurations for capturing critical structural features of forest canopy surface. By contrast, simulated VHR imagery from 3-D radiative transfer models (RTM) can explore the full range of spatial, spectral, and sun-sensor configurations to identify factors that contribute to uncertainties in stereo-derived estimates of forest canopy structure. We developed a novel method to simulate VHR stereopairs using the discrete anisotropic radiative transfer (DART) model and then derive surface elevations from the simulated images. We reconstructed one open-canopy and one closed-canopy forest scene and created a reference digital surface model/digital terrain model (DSM/DTM) using airborne small-footprint lidar points over the study sites. The VHR simulations were configured to match three independent WorldView stereopairs. The results showed that, compared to the reference DSM, the surface elevations derived using simulated and WorldView image data were consistent, with differences of <1.6 m in vertical bias, < 1 m in root mean square error (RMSE), and < 0.07 in correlation coefficient (R). We demonstrated that realistic 3-D RTM simulations could be georeferenced with a camera model for DSM generation from simulated stereopairs. This work will support a follow-up investigation that examines stereo-derived DSM quality over a broad range of surface types and acquisition parameters to suggest optimal configurations for actual VHR stereo data acquisition of vegetation canopy surfaces.

Altered Allocation of Vertical Attention in Individuals With Autism Spectrum Disorder.

Typical adults most frequently orient their attention to other people's eyes, whereas individuals with autism spectrum disorder (ASD) orient their attention to other people's mouths. Typical adults also reveal visuospatial biases on tasks such as vertical and horizontal line bisections. Therefore, the difference in face viewing might be related to a more general group difference in the allocation of vertical attention. To use vertical line bisection and quadrisection tasks to evaluate whether individuals with ASD have a more downward-oriented vertical attentional bias than do typical individuals. We recruited 20 individuals with ASD and 20 control participants matched for age (6-23 years), IQ, and sex. We asked the individuals to bisect and quadrisect lines on the top and bottom when the vertical lines were placed at the intersection of their right, left, and center egocentric sagittal planes and their coronal plane. The distances from the true midpoint and quadripoint were measured, and between-group performances were compared. No significant difference was found between the ASD and control groups for vertical line bisections or lower line quadrisections. However, when the ASD group was compared with the control group for higher line quadrisections, the ASD group exhibited a greater upward deviation. There is no downward vertical attentional spatial bias associated with ASD that could help to explain these individuals' attentional bias toward the mouth. However, additional studies are required to learn if this atypical upward vertical attentional bias might account for some of the symptoms and signs associated with ASD.

Children and adults exhibit a common vertical attention bias for object tops and scene bottoms.

Adults have a vertical attention bias (VAB) that directs their focus toward object tops and scene bottoms. This is consistent with focusing attention on the informative aspects and affordances of the environment, and generally favoring a downward gaze. The smaller size of children, combined with their relatively limited interactions with objects and scenes, could lead them to have diminished bias that only gradually develops. Alternatively, an early coupling of attention to action space could lead to VAB similar to adults. The current study investigates the developmental timeline of VAB, comparing 4-7-year-olds to adults. Participants (N = 50 children, 53 adults; 58% White, 22% Asian, 6% Black, 2% Native American, and 12% other) observed naturalistic photographic triptychs (48 objects, 52 scenes, all online). They made similarity judgments comparing a test figure to two flanking figures containing either the same top or same bottom. We found that (a) children and adults exhibit a common VAB for object tops and scene bottoms and (b) the adult bias is stronger than children's. Exploratory analyses revealed the same age trend within children, with VAB increasing with age, and asymptoting at the adult level at age 8. This demonstrates that despite age and body size differences that could make the environment for young children relatively disparate from adults, their perceptual system is already largely attuned to their individual interactive action space, with only minor continuing residual development. The findings support that, like adults, young children focus their attention on their action space and body level affordances, where they interact more with tops of objects and bottoms of scenes. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Transitions in Xenes between excitonic, topological and trivial insulator phases: Influence of screening, band dispersion and external electric field

Using a variational approach, the binding energies E_bEb of the lowest bound excitons in Xenes under varying electric field are investigated. The internal exciton motion is described both by Dirac electron dispersion and in effective-mass approximation, while the screened electron-hole attraction is modeled by a Rytova-Keldysh potential with a 2D electronic polarizability \alpha_{2D}α2D. The most important parameters as spin-orbit-induced gap E_gEg, Fermi velocity v_FvF and \alpha_{2D}α2D are taken from ab initio density functional theory calculations. In addition, \alpha_{2D}α2D is approximated in two different ways. The relation of E_bEb and E_gEg is ruled by the screening. The existence of an excitonic insulator phase with E_b&amp;gt;E_gEb&gt;Eg sensitively depends on the chosen \alpha_{2D}α2D. The values of E_gEg and \alpha_{2D}α2D are strongly modified by a vertical external electric bias UU, which defines a transition from the topological into a trivial insulator at U=E_g/2U=Eg/2, with the exception of plumbene. Within the Dirac approximation, but also within the effective mass description of the kinetic energy, the treatment of screening dominates the appearance or non-appearance of an excitonic insulator phase. Gating does not change the results: the prediction done at zero electric field is confirmed when a vertical electric field is applied. Finally, Many-Body perturbation theory approaches based on the Green’s function method, applied to stanene, confirm the absence of an excitonic insulator phase, thus validating our results obtained by ab initio modeling of \alpha_{2D}α2D.

Reducing vertical bias and error in tidal marsh digital elevation models with machine learning and LiDAR derivatives

The vertical bias and uncertainty of LiDAR-derived elevation data in tidal marshes is a major challenge for researchers in these critical ecosystems. Small positive bias errors in land surface elevation can lead to large underestimates of coastal inundation. Previous studies have shown that the bias and uncertainty of elevation data can be reduced using a variety of statistical techniques. However, many studies cover a relatively small extent, cover a large extent at coarse resolution, or rely on local data products that may not be widely available or are of unknown quality. This study aimed to develop and compare bias reduction approaches for digital elevation models (DEMs) using LiDAR derivatives in tidal marshes along Delaware Bay, Delaware, USA, a region that experiences high rates of relative sea-level rise and frequent coastal flooding. In this study, several statistical and machine-learning approaches were evaluated based on their ability to reduce vertical DEM error using field GPS survey data and LiDAR and terrain derivatives as inputs. The evaluated approaches for reducing DEM error included ensembles of multiple linear regressions, kernel-K Nearest Neighbors, gradient boosted regression trees, random forests, and deep neural networks (DNNs), which were compared based on statistical performance metrics. An ensemble of deep neural networks performed best at removing vertical DEM bias and reducing DEM uncertainty, though other approaches also performed well. GPS survey data indicated a mean absolute error, mean bias, and root mean square error in GPS surveys of 11.9 cm, 10.9, and 14.8 cm, respectively, in the original DEM. These error metrics were reduced to 3.5 cm, −0.2 cm, and 5.1 cm in the DNN ensemble-corrected DEM. The DNN ensemble was then applied to all tidal marshes throughout the study area. This corrected DEM clearly showed how interpretations of marsh platform inundation based on uncorrected DEM surfaces could be misguided. The approach used in this study only requires LiDAR-derived products and field surveys, so it may be applied readily in other regions.

Continuously Updated Digital Elevation Models (CUDEMs) to Support Coastal Inundation Modeling

The National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI) generates digital elevation models (DEMs) that range from the local to global scale. Collectively, these DEMs are essential to determining the timing and extent of coastal inundation and improving community preparedness, event forecasting, and warning systems. We initiated a comprehensive framework at NCEI, the Continuously Updated DEM (CUDEM) Program, with seamless bare-earth, topographic-bathymetric and bathymetric DEMs for the entire United States (U.S.) Atlantic and Gulf of Mexico Coasts, Hawaii, American Territories, and portions of the U.S. Pacific Coast. The CUDEMs are currently the highest-resolution, seamless depiction of the entire U.S. Atlantic and Gulf Coasts in the public domain; coastal topographic-bathymetric DEMs have a spatial resolution of 1/9th arc-second (~3 m) and offshore bathymetric DEMs coarsen to 1/3rd arc-second (~10 m). We independently validate the land portions of the CUDEMs with NASA’s Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) observatory and calculate a corresponding vertical mean bias error of 0.12 m ± 0.75 m at one standard deviation, with an overall RMSE of 0.76 m. We generate the CUDEMs through a standardized process using free and open-source software (FOSS) and provide open-access to our code repository. The CUDEM framework consists of systematic tiled geographic extents, spatial resolutions, and horizontal and vertical datums to facilitate rapid updates of targeted areas with new data collections, especially post-storm and tsunami events. The CUDEM framework also enables the rapid incorporation of high-resolution data collections ingested into local-scale DEMs into NOAA NCEI’s suite of regional and global DEMs. Future research efforts will focus on the generation of additional data products, such as spatially explicit vertical error estimations and morphologic change calculations, to enhance the utility and scientific benefits of the CUDEM Program.

Tuned drop-shape magnetophoretic conductors for controlled single-particle transport in microfluidic chips

In recent years, lab-on-a-chip devices have attracted many researchers due to their numerous advantages, making them suitable for important bioapplications. One of the key challenges in this field is manipulating a group of particles and cells at single-particle resolution. Different techniques have been proposed to tackle this challenge; however, none of them offer the controllability and scalability required in most bioapplications. Recently, drop-shape magnetophoretic circuits have been introduced as an advanced technique for the precise transport of a great number of particles simultaneously. However, in moving along the magnetic track, the particles experience a sudden jump from one magnet to the next one, which may not be in a highly controlled fashion and can be problematic. To overcome this issue, in the current work, we introduce a new design equipped with a tuning gate electrode added to the blind spots of the magnetophoretic conductor. This design transports the particles in a tri-axial magnetic field, with a vertical bias field that reduces the attraction force between particles and inhibits the particle cluster formation. We study the effect of straight and curved current-carrying gates and show that they positively affect the resulting magnetic energy. Based on our finite element method, we found the curved gate offers controlled smooth particle transport at lower electrical currents. We fabricate the proposed chip based on this design and show that the experimental results agree well with the simulation predictions. The introduced design enhances the reliability of the magnetophoretic circuits operating in a tri-axial magnetic field and makes them good candidates for fundamental applications in single-cell biology and medicine.

Comparing the impact of the method of adjustment and forced-choice methodologies on subjective visual vertical bias and variability.

Previous research suggested that the method of adjustment and forced choice variants of the subjective visual vertical (SVV) produce comparable estimates of both bias and variability. However, variants of the SVV that utilize a method of adjustment procedure are known to be heavily influenced by task parameters, including the stimulus rotation speed, which was not accounted for in previous SVV research comparing the method of adjustment to forced-choice. The aim of the present study was to determine if (1) the SVV with a forced-choice procedure produces both bias and variability estimates that are comparable to those obtained using a method of adjustment procedure, (2) to see if rotation speed impacts the comparability of estimates and (3) quantify correlations between the estimates produced by different procedures. Participants completed a variant of the SVV which utilized a forced-choice procedure as well as two variants of the SVV using a method of adjustment procedure with two different rotation speeds (6°/s and 12°/s). We found that the bias estimates were similar across all three conditions tested and that the variability estimates were greater in the SVV variants that utilized a method of adjustment procedure. This difference was more pronounced when the rotation speed was slower (6°/s). The results of this study suggest that forced-choice and method of adjustment methodologies yield similar bias estimates and different variability estimates. Given these results, we recommend utilizing forced-choice procedures unless (a) forced-choice is not feasible or (b) response variability is unimportant. We also recommend that clinicians consider the SVV methods when interpreting a patient's test results, especially for variability metrics.