Electrical stimulation of visual cortex can immediately improve spatial vision

Published in final edited form as:Curr Biol. 2016 July 25; 26(14): 1867–1872. doi:10.1016/j.cub.2016.05.019.SUMMARY We can improve human vision by correcting the optics of our lenses [1, 2, 3]. However, after the eye transduces the light, visual cortex has its own limitations that are challenging to correct [4]. Overcoming these limitations has typically involved innovative training regimes that improve vision across many days [5, 6]. In the present study, we wanted to determine whether it is possible to immediately improve the precision of spatial vision with noninvasive direct-current stimulation. Previous work suggested that visual processing could be modulated with such stimulation [7, 8, 9]. However, the short duration and variability of such effects made it seem unlikely that spatial vision could be improved for more than several minutes [7, 10]. Here we show that visual acuity in the parafoveal belt can be immediately improved by delivering noninvasive direct current to visual cortex. Twenty minutes of anodal stimulation improved subjects’ vernier acuity by approximately 15% and increased the amplitude of the earliest visually evoked potentials in lockstep with the behavioral effects. When we reversed the orientation of the electric field, we impaired resolution and reduced the amplitude of visually evoked potentials. Next, we found that anodal stimulation improved acuity enough to be measurable with the relatively coarse Snellen test and that subjects with the poorest acuity benefited the most from stimulation. Finally, we found that stimulation-induced acuity improvements were accompanied by changes in contrast sensitivity at high spatial frequencies.This work was supported by grants from the NIH (R01-EY019882, R01-EY025275, P30-EY08126, T32-EY007135, F31-MH102042). We thank the reviewers and Randolph Blake for helpful comments. We thank Kevin Dieter for technical assistance in designing the psychophysical procedure for experiment 5. Subjects gave informed written consent to procedures approved by the Vanderbilt University Institutional Review Board and were compensated at a rate of $10/hr for their time. (R01-EY019882 - NIH; R01-EY025275 - NIH; P30-EY08126 - NIH; T32-EY007135 - NIH; F31-MH102042 - NIH)Accepted manuscrip

Development and visualization of a risk prediction model for metabolic syndrome: a longitudinal cohort study based on health check-up data in China

AimOur study aimed to construct a practical risk prediction model for metabolic syndrome (MetS) based on the longitudinal health check-up data, considering both the baseline level of physical examination indicators and their annual average cumulative exposure, and to provide some theoretical basis for the health management of Mets.MethodsThe prediction model was constructed in male and female cohorts, separately. The shared set of predictive variables screened out from 49 important physical examination indicators by the univariate Cox model, Lasso-Cox model and the RSF algorithm collectively was further screened by Cox stepwise regression method. The screened predictors were used to construct prediction model by the Cox proportional hazards regression model and RSF model, respectively. Subsequently, the better method would be selected to develop final MetS predictive model according to comprehensive comparison and evaluation. Finally, the optimal model was validated internally and externally by the time-dependent ROC curve (tdROC) and concordance indexes (C-indexes). The constructed predictive model was converted to a web-based prediction calculator using the “shiny” package of the R4.2.1 software.ResultsA total of 15 predictors were screened in the male cohort and 9 predictors in the female cohort. In both male and female cohorts, the prediction error curve of the RSF model was consistently lower than that of the Cox proportional hazards regression model, and the integrated Brier score (IBS) of the RSF model was smaller, therefore, the RSF model was used to develop the final prediction model. Internal validation of the RSF model showed that the area under the curve (AUC) of tdROC for 1 year, 3 years and 5 years in the male cohort were 0.979, 0.991, and 0.983, and AUCs in the female cohort were 0.959, 0.975, and 0.978, respectively, the C-indexes calculated by 500 bootstraps of the male and female cohort RSF models are above 0.7. The external validation also showed that the model has good predictive ability.ConclusionThe risk predictive model for MetS constructed by RSF in this study is more stable and reliable than Cox proportional hazards regression model, and the model based on multiple screening of routine physical examination indicators has performed well in both internal and external data, and has certain clinical application value

Characteristics of Dissolved Organic Matter Impacted by Different Land Use in Haihe River Watershed, China

It is important to explore characteristics of dissolved organic matter (DOM) in the riverine system due to its critical role in the carbon cycle. This study investigated the distribution characteristics and sources of DOM based on excitation emission matrix three-dimensional fluorescence technology and parallel factor (EEM-PARAFAC) analysis at two rivers in northern China strongly impacted by human activities. The results show that the fluorescence intensity of terrestrial humic-like substances increased during summer in Haihe River. The intensity was significantly higher than in spring due to terrestrial detritus from runoff conveyance. The fluorescence intensity of protein-like substances in spring was the highest and decreased in summer. This feature of DOM in the Duliujian River was related to the increase in precipitation and surface runoff in the wet season and the rapid degradation of mixed DOM in the dry season. An analysis of HIX, BIX and FI showed a low degree of DOM humification and more endogenous contributions from microbial and phytoplankton degradation. Seasonal variations of dissolved organic carbon (DOC) and chromophoric DOM (CDOM, a335, thereinto C1) suggest that chromophores, particularly terrestrial substances, regulate the temporal patterns of DOM in the two rivers. Combined with the analysis of the proportion of land use types in riparian buffers, tillage had a great impact on DOM content and hydrophobicity in Haihe River watershed. Domestic wastewater and industrial sewage discharge contribute more DOM to Duliujian River watershed, which was indicated by more abundant protein-like components (212.17 ± 94.63 QSU in Duliujian River;186.59 ± 238.72 QSU in Haihe River). This study highlights that different land use types resulted in distinctive sources and seasonal dynamics of DOM in rivers. Meanwhile, it should be considered that the estimation of carbon cycling should involve monitoring and evaluating anthropogenic inputs into rivers

An Adaptive Approach for Voltage Sag Automatic Segmentation

Voltage sag characterization is essential for extracting information about a sag event’s origin and how sag events impact sensitive equipment. In response to such needs, more characteristics are required, such as the phase-angle jump, point-on-wave, unbalance, and sag type. However, the absence of an effective automatic segmentation method is a barrier to obtaining these characteristics. In this paper, an automatic segmentation method is proposed to improve this situation. Firstly, an extended voltage sag characterization method is described, in which segmentation plays an important role. Then, a multi-resolution singular value decomposition method is introduced to detect the boundaries of each segment. Further, the unsolved problem of how to set a threshold adaptively for different waveforms is addressed, in which the sag depth, the mean square error, and the entropy of the sag waveform are considered. Simulation data and field measurements are utilized to validate the effectiveness and reliability of the proposed method. The results show that the accuracies of both boundary detection and segmentation obtained using the proposed method are higher than those obtained using existing methods. In general, the proposed method can be implemented into a power quality monitoring system as a preprocess to support related research activities

Preparation and characterization of oriented hydroxyapatite bundles in supersaturated solution: conic interference and charge balance

Hydroxyapatite (HA), an artificial bioceramic with high similarity to the mineral constituent of vertebrate bones and teeth, has attracted extensive attention due to its excellent bioactivity and biocompatibility. The micro-nano structure of HA is a vital factor in expanding its application in biomedicine as well as in many other industrial fields. What's more, HA nanofiber exhibits outstanding properties among its various morphologies. In this work, HA bundles with the same oriented nanofibers are successfully synthesized in a solvothermal reaction system by controlling the amount of carbonate addition and using oleic acid as a template. Under the synergistic effect of different molar ratios of hydroxide ion to carbanion ([OH−]/[CO32−]), HA nanofibers gradually increase their aspect ratio and tend to grow into oriented bundles. This product has admirable flexibility and good mechanical strength, as well as great application potential. Based on the characterization and analysis results, we take a further exploration of the effects of ionic interference ([OH−]/[CO32−]) and charge balance (CO32− vs PO43, Na + vs Ca2+) on the microstructure, phase composition and thermal stability of HA nanofibers bundles (HANBs) in the solvothermal system during the chemical reaction process. And then, the formation and assembly mechanism of HANBs is proposed, and the role of van der Waals forces in this process is also discussed. Furthermore, the generation of this clustered state may be influenced by the shift in the dissolution equilibrium of insoluble carbonates during synthesis. This research provides a new direction for controlling the micro-nano morphology of HA to further obtain products with desirable properties

Impact of public hospital pricing reform on medical expenditure structure in Jiangsu, China: a synthetic control analysis

Background: The synthetic control method (SCM) is a useful tool in providing unbiased analysis on the policy effect in real-world health policy evaluations. Through controlling for a few confounding factors, we aim to apply SCM in analyzing the impact of the pricing reform on medical expenditure structure in Jiangsu Province, China. Methods: We constructed a synthetic control for Zhenjiang, a city where the reform was piloted in Jiangsu, by selecting weights on those potential control units to define a linear combination of the control outcomes to replicate the counterfactual as if the intervention is in absence. The policy effect was measured by the differences in the percentage of drug expenditure among average outpatient and inpatient care cost per visit in the post-policy period between Zhenjiang and its synthetic control. We also examined the significance of the estimated results by performing placebo tests, and cross-validated the results with a difference-in-differences analysis. Results: The medical pricing reform was found to be effective in reducing the drug expenditure proportions in both outpatient and inpatient care by an estimated mean level of 7.7 and 3.2% (or 16.3 and 9.2% relative decrease to their 2012 levels) respectively. This reform effect was estimated to be significant in the placebo tests and was further confirmed by a cross-validation. Conclusion: We conclude that the pricing reform in public hospitals has significantly reduced drug expenditure incurred in both outpatient and inpatient care. This study also highlights the applicability of SCM method as an effective tool for health policy evaluation using publicly available data in the context of Chinese healthcare system.Medicine, Faculty ofOther UBCNon UBCPopulation and Public Health (SPPH), School ofReviewedFacult

Seasonal Variations of Dissolved Organic Matter in Urban Rivers of Northern China

Dissolved organic matter (DOM) is ubiquitously present in aquatic environments, playing an important role in the global carbon cycle and water quality. It is necessary to reveal the potential sources and explore spatiotemporal variation of DOM in rivers, especially in urban zones impacted by human activities. It was designed to aim to explore spatiotemporal variations of DOM in urban rivers and ascertain the influencing factors. In this study, dissolved organic carbon (DOC) concentrations, UV-Vis absorption spectroscopy, and 3D fluorescence spectroscopy combined with parallel factor analysis were utilized to characterize DOM composition in urban rivers (the Jiyun, Chaobai, and Yongding rivers) in Tianjin city, northern China. The results showed that DOC (1.28 to 25.85 mg·L−1), generally, was at its highest level in spring, followed by summer, and lowest in autumn and winter, and that the absorption parameters E250:365 (condensation degree/molecular weight, 7.88), SUVA254 (aromaticity, 3.88 L mg C−1 m−1), a355 (content of chromophores, 4.34 m−1), a260 (hydrophobicity, 22.02 m−1), and SR (molecular weight, 1.08) of CDOM (chromophoric DOM) suggested that DOM is mainly composed of low-molecular-weight fulvic acid and protein-like moieties, and had the capability of participating in pollutant migrations and transformations. The results demonstrated significant seasonal differences. Generally, high DOC content was detected in rivers in urban suburbs, due to anthropogenic inputs. Three fluorescence components were identified, and the fluorescence intensity of the protein class reached the highest value, 294.47 QSU, in summer. Different types of land use have different effects on the compositions of riverine DOM; more protein-like DOM was found in sections of urban rivers. The correlation between DOC concentration and the CDOM absorption coefficient was found to be unstable due to deleterious input from industrial and agricultural wastewater and from domestic sewage from human activities. HIX and BIX elucidated that the source of CDOM in three river watersheds was influenced by both terrestrial and autochthonous sources, and the latter prevailed over the former. Geospatial data analysis indicated that CDOM in autumn was sourced from plant detritus degradation from forest land or from the urban green belt; construction land had a great influence on DOC and CDOM in riparian buffer areas. It was revealed that DOM in the watershed is highly impacted by nature and human activities through land use, soil erosion, and surface runoff/underground percolation transport; domestic sewage discharge constituted the primary source and was the greatest determiner among the impacts

Reactor Core Design and Analysis for a Micronuclear Power Source

Underwater vehicle is designed to ensure the security of country sea boundary, providing harsh requirements for its power system design. Conventional power sources, such as battery and Stirling engine, are featured with low power and short lifetime. Micronuclear reactor power source featured with higher power density and longer lifetime would strongly meet the demands of unmanned underwater vehicle power system. In this paper, a 2.4 MWt lithium heat pipe cooled reactor core is designed for micronuclear power source, which can be applied for underwater vehicles. The core features with small volume, high power density, long lifetime, and low noise level. Uranium nitride fuel with 70% enrichment and lithium heat pipes are adopted in the core. The reactivity is controlled by six control drums with B4C neutron absorber. Monte Carlo code MCNP is used for calculating the power distribution, characteristics of reactivity feedback, and core criticality safety. A code MCORE coupling MCNP and ORIGEN is used to analyze the burnup characteristics of the designed core. The results show that the core life is 14 years, and the core parameters satisfy the safety requirements. This work provides reference to the design and application of the micronuclear power source

Power disturbance waveform analysis and proactive application in power systems

Abstract Power disturbances, defined as the waveform distortion of a power system under normal or abnormal conditions, contain considerable system and equipment state information. Obtaining equipment and system state information from power disturbance is very important to ensure the safety of power grids. To adapt to the development of power electronics, informatisation and digitisation of power systems, several applications with waveform‐recording devices have obtained large amounts of disturbance waveform data, laying an important foundation for the analysis and application of power disturbance waveform data. First, typical disturbance waveform monitoring devices and a disturbance trigger detection algorithm are introduced. Then, disturbances are classified as switching, fault, or abnormal operations, according to the cause. The characteristics of various typical disturbance waveform data were analysed by combining the simulation and measured data. This paper summarises the application analysis of power disturbance waveform data at both the system and equipment levels. Finally, the construction scheme of a power disturbance waveform data monitoring and analysis platform for two different application scenarios was proposed for commutation failure monitoring and medium‐voltage distribution network fault warning. The research conducted here is expected to support the construction of a power disturbance waveform analysis platform