Fundamental‐mode basin oscillations in the Japan/East Sea

We present observational evidence from coastal tide station and bottom pressure data that basin‐mode oscillations are frequently excited in the Japan/East Sea (JES). The fundamental basin‐mode is a Kelvin‐wave‐like oscillation consisting of a single amphidromic system around which the high water propagates counter‐clockwise. Its period is about 6.7 hours and its coastal wavelength is equivalent to the circumference of the JES. The relative amplitudes of the observed oscillations agree with Rikiishi\u27s 1986 model results except for stations near the Korea Strait where the closed boundary in the model produces unrealistically high amplitudes. The basin oscillation amplitude varies on synoptic time scales (2–17 days) and exhibits seasonal variations. The optimal wind direction to generate basin‐mode oscillations is along 60°/240° T

Efficient Language Model Architectures for Differentially Private Federated Learning

Cross-device federated learning (FL) is a technique that trains a model on data distributed across typically millions of edge devices without data leaving the devices. SGD is the standard client optimizer for on device training in cross-device FL, favored for its memory and computational efficiency. However, in centralized training of neural language models, adaptive optimizers are preferred as they offer improved stability and performance. In light of this, we ask if language models can be modified such that they can be efficiently trained with SGD client optimizers and answer this affirmatively. We propose a scale-invariant Coupled Input Forget Gate (SI CIFG) recurrent network by modifying the sigmoid and tanh activations in the recurrent cell and show that this new model converges faster and achieves better utility than the standard CIFG recurrent model in cross-device FL in large scale experiments. We further show that the proposed scale invariant modification also helps in federated learning of larger transformer models. Finally, we demonstrate the scale invariant modification is also compatible with other non-adaptive algorithms. Particularly, our results suggest an improved privacy utility trade-off in federated learning with differential privacy

Rapid Variability in the Japan/East Sea: Basin Oscillations, Internal Tides, and Near-Inertial Oscillations

Many processes contribute to the variations of currents, sea surface height (SSH), and thermocline depth in marginal seas. Energetic examples range broadly over time scales from slow mesoscale and interannual variations to rapid basin oscillations, internal tides, and near-inertial oscillations. Our measurement array in the Japan/East Sea (JES) offered a special opportunity to study these processes simultaneously, revealing important interconnections among them

Diagnosis and Prognosis Using Machine Learning Trained on Brain Morphometry and White Matter Connectomes

Accurate, reliable prediction of risk for Alzheimer’s disease (AD) is essential for early, diseasemodifying therapeutics. Multimodal MRI, such as structural and diffusion MRI, is likely to contain complementary information of neurodegenerative processes in AD. Here we tested the utility of commonly available multimodal MRI (T1-weighted structure and diffusion MRI), combined with high-throughput brain phenotyping—morphometry and connectomics—and machine learning, as a diagnostic tool for AD. We used, firstly, a clinical cohort at a dementia clinic (study 1: Ilsan Dementia Cohort; N=211; 110 AD, 64 mild cognitive impairment [MCI], and 37 subjective memory complaints [SMC]) to test and validate the diagnostic models; and, secondly, Alzheimer’s Disease Neuroimaging Initiative (ADNI)-2 (study 2) to test the generalizability of the approach and the prognostic models with longitudinal follow up data. Our machine learning models trained on the morphometric and connectome estimates (number of features=34,646) showed optimal classification accuracy (AD/SMC: 97% accuracy, MCI/SMC: 83% accuracy; AD/MCI: 97% accuracy) with iterative nested cross-validation in a single-site study, outperforming the benchmark model (FLAIR-based white matter hyperintensity volumes). In a generalizability study using ADNI-2, the combined connectome and morphometry model showed similar or superior accuracies (AD/HC: 96%; MCI/HC: 70%; AD/MCI: 75% accuracy) as CSF biomarker model (t-tau, p-tau, and Amyloid β, and ratios). We also predicted MCI to AD progression with 69% accuracy, compared with the 70% accuracy using CSF biomarker model. The optimal classification accuracy in a single-site dataset and the reproduced results in multisite dataset show the feasibility of the high-throughput imaging analysis of multimodal MRI and data-driven machine learning for predictive modeling in AD

OXYGEN REACTIVE POLYMERS FOR TREATMENT OF TRAUMATIC BRAIN INJURY

Methods and compositions for treating traumatic brain injury . The methods and compositions utilize a multi - functional oxygen reactive polymer ( ORP ) that includes repeating units that include a reactive oxygen species ( ROS ) scavenging group and a polyalkylene oxide group . For theranostic applications , the oxygen reactive polymer fur ther includes a diagnostic group

Trichloroethylene Hypersensitivity Syndrome: A Disease of Fatal Outcome

Trichloroethylene is commonly used as an industrial solvent and degreasing agent. The clinical features of acute and chronic intoxication with trichloroethylene are well-known and have been described in many reports, but hypersensitivity syndrome caused by trichloroethylene is rarely encountered. For managing patients with trichloroethylene hypersensitivity syndrome, avoiding trichloroethylene and initiating glucocorticoid have been generally accepted. Generally, glucocorticoid had been tapered as trichloroethylene hypersensitivity syndrome had ameliorated. However, we encountered a typical case of trichloroethylene hypersensitivity syndrome refractory to high dose glucocorticoid treatment. A 54-year-old Korean man developed jaundice, fever, red sore eyes, and generalized erythematous maculopapular rashes. A detailed history revealed occupational exposure to trichloroethylene. After starting intravenous methylprednisolone, his clinical condition improved remarkably, but we could not reduce prednisolone because his liver enzyme and total bilirubin began to rise within 2 days after reducing prednisolone under 60 mg/day. We recommended an extended admission for complete recovery, but the patient decided to leave the hospital against medical advice. The patient visited the emergency department due to pneumonia and developed asystole, which did not respond to resuscitation

Effects of molecular contamination and sp2^2 carbon on oxidation of (100) single-crystal diamond surfaces

The efficacy of oxygen (O) surface terminations of specific moieties and densities on diamond depends on factors such as crystallinity, roughness, and crystal orientation. Given the wide breadth of diamond-like materials and O-termination techniques, it can be difficult to discern which method would yield the highest and most consistent O coverage on a particular subset of diamond. We first review the relevant physical parameters for O-terminating single-crystalline diamond (SCD) surfaces and summarize prior oxidation work on (100) SCD. We then report on our experimental study on X-ray Photoelectron Spectroscopy (XPS) characterization of (100) diamond surfaces treated with oxidation methods that include wet chemical oxidation, photochemical oxidation with UV illumination, and steam oxidation using atomic layer deposition. We describe a rigorous XPS peak-fitting procedure for measuring the functionalization of O-terminated samples and recommend that the reporting of peak energy positions, line shapes, and full-width-half-maximum values of the individual components, along with the residuals, are important for evaluating the quality of the peak fit. Two chemical parameters on the surface, sp$^2$ C and molecular contaminants, are also crucial towards interpreting the O coverage on the diamond surface and may account for the inconsistency in prior reported values in literature

The role of nanopores on U(VI) sorption and redox behavior in U(VI)-contaminated subsurface sediments

Most reactive surfaces in clay-dominated sediments are present within nanopores (pores of nm dimension). The behavior of geological fluids and minerals in nanopores is significantly different from those in normal non-nanoporous environments. The effect of nanopore surfaces on U(VI) sorption/desorption and reduction is likely to be significant in clay-rich subsurface environments. Our research results from both model nanopore system and natural sediments from both model system (synthetic nanopore alumina) and sediments from the ORNL Field Research Center prove that U(VI) sorption on nanopore surfaces can be greatly enhanced by nanopore confinement environments. The results from the project provide advanced mechanistic, quantitative information on the physiochemical controls on uranium sorption and redox behavior in subsurface sediments. The influence of nanopore surfaces on coupled uranium sorption/desorption and reduction processes is significant in virtually all subsurface environments, because most reactive surfaces are in fact nanopore surfaces. The results will enhance transfer of our laboratory-based research to a major field research initiative where reductive uranium immobilization is being investigated. Our results will also provide the basic science for developing in-situ colloidal barrier of nanoporous alumina in support of environmental remediation and long term stewardship of DOE sites