Quality Control and Tilt Correction Effects on the Turbulent Fluxes Observed at an Ocean Platform

This study investigates atmospheric factors influencing the quality and the postprocessing (e.g., tilt correction) of fast-response measurements of turbulent fluxes for difficult open-sea measurements over an offshore platform. The data were collected at the Ieodo Ocean Research Station over the Yellow Sea during the period from 5 November 2007 to 19 February 2008. The quality control removal of the data generally depends on wind speed, relative humidity, significant wave height, visibility, and stability. The removal of substantial water vapor data with weak-wind stable conditions is investigated. Three different tilt correction algorithms (double rotation, triple rotation, and planar fit) are applied to correct the data because of inadvertent tilt of sonic anemometers. The choice of tilt correction method significantly influences the angle between the wind and stress direction.Keywords: Turbulence, Fluxe

Clinical Characteristics of a Nationwide Hospital-based Registry of Mild-to-Moderate Alzheimer's Disease Patients in Korea: A CREDOS (Clinical Research Center for Dementia of South Korea) Study

With rapid population aging, the socioeconomic burden caused by dementia care is snowballing. Although a few community-based studies of Alzheimer's disease (AD) have been performed in Korea, there has never been a nationwide hospital-based study thereof. We aimed to identify the demographics and clinical characteristics of mild-to-moderate AD patients from the Clinical Research Center for Dementia of Korea (CREDOS) registry. A total of 1,786 patients were consecutively included from September 2005 to June 2010. Each patient underwent comprehensive neurological examination, interview for caregivers, laboratory investigations, neuropsychological tests, and brain MRI. The mean age was 74.0 yr and the female percentage 67.0%. The mean period of education was 7.1 yr and the frequency of early-onset AD (< 65 yr old) was 18.8%. Among the vascular risk factors, hypertension (48.9%) and diabetes mellitus (22.3%) were the most frequent. The mean score of the Korean version of Mini-Mental State Examination (K-MMSE) was 19.2 and the mean sum of box scores of Clinical Dementia Rating (CDR-SB) 5.1. Based on the well-structured, nationwide, and hospital-based registry, this study provides the unique clinical characteristics of AD and emphasizes the importance of vascular factors in AD in Korea

Prediction of cognitive impairment via deep learning trained with multi-center neuropsychological test data

Background Neuropsychological tests (NPTs) are important tools for informing diagnoses of cognitive impairment (CI). However, interpreting NPTs requires specialists and is thus time-consuming. To streamline the application of NPTs in clinical settings, we developed and evaluated the accuracy of a machine learning algorithm using multi-center NPT data. Methods Multi-center data were obtained from 14,926 formal neuropsychological assessments (Seoul Neuropsychological Screening Battery), which were classified into normal cognition (NC), mild cognitive impairment (MCI) and Alzheimers disease dementia (ADD). We trained a machine learning model with artificial neural network algorithm using TensorFlow (https://www.tensorflow.org) to distinguish cognitive state with the 46-variable data and measured prediction accuracies from 10 randomly selected datasets. The features of the NPT were listed in order of their contribution to the outcome using Recursive Feature Elimination. Results The ten times mean accuracies of identifying CI (MCI and ADD) achieved by 96.66 ± 0.52% of the balanced dataset and 97.23 ± 0.32% of the clinic-based dataset, and the accuracies for predicting cognitive states (NC, MCI or ADD) were 95.49 ± 0.53 and 96.34 ± 1.03%. The sensitivity to the detection CI and MCI in the balanced dataset were 96.0 and 96.0%, and the specificity were 96.8 and 97.4%, respectively. The time orientation and 3-word recall score of MMSE were highly ranked features in predicting CI and cognitive state. The twelve features reduced from 46 variable of NPTs with age and education had contributed to more than 90% accuracy in predicting cognitive impairment. Conclusions The machine learning algorithm for NPTs has suggested potential use as a reference in differentiating cognitive impairment in the clinical setting.The publication costs, design of the study, data management and writing the manuscript for this article were supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2017S1A6A3A01078538), Korea Ministry of Health & Welfare, and from the Original Technology Research Program for Brain Science through the National Research Foundation of Korea funded by the Korean Government (MSIP; No. 2014M3C7A1064752)

Characterizing the signature of a spatio-temporal wind wave field

This study aims at characterizing the distinctive features of a spatio-temporal nonlinear wave surface. We analyze wind-generated 3-D wave fields observed during the passage of an atmospheric front, which led to a wide directional spreading of wave energy. Data were acquired from the ocean research station Socheongcho-ORS (Yellow Sea) with a stereo wave imaging system. They include 3-D (i.e. 2-D + time) measurements of the sea surface elevation with high spatial and temporal resolution over a swath larger than any previous similar deployment. We examine the shape and the nonlinear properties of the wavenumber/frequency 3-D wave spectrum, and the characteristic spatial, temporal and spatio-temporal length scales of the wave field. We then focus on analyzing the probability of occurrence and the spatio-temporal size of the rogue waves we identified in the data. In particular, we provide for the first time an empirical estimate of the extent of the horizontal sea surface spanned by rogue waves. We also propose and assess a novel strategy to determine from the 3-D wave spectrum the vertical current profile, to be then used to map the spectrum on intrinsic frequencies

Mutational analysis of the ATP-binding site in HslU, the ATPase component of HslVU protease in Escherichia coli

AbstractHslU is the ATPase component of the ATP-dependent HslVU protease in Escherichia coli. To gain an insight into the structure and function of HslU, site-directed mutagenesis was performed to generate a mutation in the ATP-binding site of the ATPase (i.e., to replace the Lys63 with Thr). Unlike the wild-type HslU, the mutant form (referred to as HslU/K63T) could not hydrolyze ATP or support the ATP-dependent hydrolysis of N-carbobenzoxy-Gly-Gly-Leu-7-amido-4-methyl coumarin by HslV. The wild-type HslU (a mixture of monomer and dimer) formed a multimer containing 6–8 subunits in the presence of either ATP or ADP, indicating that ATP-binding, but not its hydrolysis, is required for oligomerization of HslU. However, HslU/K63T remained as a monomer whether or not the adenine nucleotides were present. Furthermore, ATP or ADP could protect HslU, but not HslU/K63T, from degradation by trypsin. These results suggest that the mutation in the ATP-binding site results in prevention of the binding of the adenine nucleotides to HslU and hence in impairment of both oligomerization and ATPase function of HslU

Microhomology Selection for Microhomology Mediated End Joining in <i>Saccharomyces cerevisiae</i>

Microhomology-mediated end joining (MMEJ) anneals short, imperfect microhomologies flanking DNA breaks, producing repair products with deletions in a Ku- and RAD52-independent fashion. Puzzlingly, MMEJ preferentially selects certain microhomologies over others, even when multiple microhomologies are available. To define rules and parameters for microhomology selection, we altered the length, the position, and the level of mismatches to the microhomologies flanking homothallic switching (HO) endonuclease-induced breaks and assessed their effect on MMEJ frequency and the types of repair product formation. We found that microhomology of eight to 20 base pairs carrying no more than 20% mismatches efficiently induced MMEJ. Deletion of MSH6 did not impact MMEJ frequency. MMEJ preferentially chose a microhomology pair that was more proximal from the break. Interestingly, MMEJ events preferentially retained the centromere proximal side of the HO break, while the sequences proximal to the telomere were frequently deleted. The asymmetry in the deletional profile among MMEJ products was reduced when HO was induced on the circular chromosome. The results provide insight into how cells search and select microhomologies for MMEJ in budding yeast

A data set of sea surface stereo images to resolve space-time wave fields

Stereo imaging of the sea surface elevation provides unique field data to investigate the geometry and dynamics of oceanic waves. Typically, this technique allows retrieving the 4-D ocean topography (3-D space + time) at high frequency (up to 15–20 Hz) over a sea surface region of area ~104 m2. Stereo data fill the existing wide gap between sea surface elevation time-measurements, like the local observation provided by wave-buoys, and large-scale ocean observations by satellites. The analysis of stereo images provides a direct measurement of the wavefield without the need of any linear-wave theory assumption, so it is particularly interesting to investigate the nonlinearities of the surface, wave-current interaction, rogue waves, wave breaking, air-sea interaction, and potentially other processes not explored yet. In this context, this open dataset aims to provide, for the first time, valuable stereo measurements collected in different seas and wave conditions to invite the ocean-wave scientific community to continue exploring these data and to contribute to a better understanding of the nature of the sea surface dynamics