Distributions of dissolved inorganic carbon and total alkalinity in the Western Arctic Ocean

The third Chinese National Arctic Research Expedition (3rd CHINARE-Arctic in 2008) was carried out from July to September 2008. During the survey, numerous sea water samples were taken for CO2 parameter measurement (including total alkalinity TA and total dissolved inorganic carbon DIC).The distribution of CO2 parameters in the Western Arctic Ocean was determined, and the controlling factors are addressed. The ranges of summertime TA, normalized TA (nTA), DIC and normalized DIC (nDIC) in the surface seawater were 1.757 - 2.229 μmol * kg(-1), 2.383 - 2.722 μmol * kg(-1), 1.681 - 2.034 μmol * kg(-1), 2.119 - 2.600 μmol * kg(-1), respectively. Because of dilution from ice meltwater, the surface TA and DIC concentrations were relatively low. TA in the upper 100 m to the south of 78±N had good correlation with salinity, showing a conservative behavior. The distribution followed the seawater-river mixing line at salinity >30, then followed the seawater mixing line (diluted by river water to salinity = 30) with the ice meltwater. The DIC distribution in the Chukchi Sea was dominated by biological production or respiration of organic matter, whereas conservative mixing dominated the mixed layer TA distribution in the ice-free Canada Basin

Summertime freshwater fractions in the surface water of the western Arctic Ocean evaluated from total alkalinity

As a quasi-conservative tracer, measures of total alkalinity (TA) can be utilized to trace the relative fractions of freshwater and seawater. In this study, based on the TA and related data collected during the third Chinese National Arctic Research Expedition (July—September 2008, 3rd CHINARE-Arctic) and the fourth Chinese National Arctic Research Expedition (July — September 2010, 4th CHINARE-Arctic), fractions of sea-ice meltwater, river runoff, and seawater within the surface water of the western Arctic Ocean were determined using salinity and TA relationships. The largest fraction of sea-ice meltwater was found around 75°N within the Canada Basin during both surveys, which is located at the ice edge. Generally, it was found that the fraction of river runoff was less than that of sea-ice meltwater. The river runoff, composed mainly of contributions from the Yukon River carried by Bering inflow water and the Mackenzie River, was influenced by the currents, leading to two peak areas of its fraction. Our results show that the dilution effect of freshwater carried by Bering inflow water during the 3rd CHINARE-Arctic in 2008 expedition period may be stronger than that during the 4th CHINARE-Arctic in 2010 expedition period. The peak area of sea-ice meltwater fraction during the 4th CHINARE-Arctic was different from that of the 3rd CHINARE-Arctic, corresponding to their sea-ice condition

The Characterization of Deqi during Moxibustion in Stroke Rats

The efficacy of acupuncture and moxibustion is closely related to Deqi phenomenons, which are some subjective feelings. However, no one has reported the objective characterization of Deqi. Our preliminary research has found a phenomenon of tail temperature increasing (TTI) obviously in some stroke rats by suspended moxibustion at the acupoint dà zhuī (DU 14), which is similar to one characterization of Deqi during moxibustion that moxibustion heat is transferred from the original moxibustion acupoint to the other areas of the body. We wonder whether TTI is the objective indicator of Deqi characterization in animals. The present study showed that the stroke rat's recovery was also associated with TTI phenomenon. This suggests that TTI phenomenon is one objective characterization of the Deqi in stroke rats. Application of the TTI phenomenon contributes to explore the physiological mechanism of Deqi

Disruption Precursor Onset Time Study Based on Semi-supervised Anomaly Detection

The full understanding of plasma disruption in tokamaks is currently lacking, and data-driven methods are extensively used for disruption prediction. However, most existing data-driven disruption predictors employ supervised learning techniques, which require labeled training data. The manual labeling of disruption precursors is a tedious and challenging task, as some precursors are difficult to accurately identify, limiting the potential of machine learning models. To address this issue, commonly used labeling methods assume that the precursor onset occurs at a fixed time before the disruption, which may not be consistent for different types of disruptions or even the same type of disruption, due to the different speeds at which plasma instabilities escalate. This leads to mislabeled samples and suboptimal performance of the supervised learning predictor. In this paper, we present a disruption prediction method based on anomaly detection that overcomes the drawbacks of unbalanced positive and negative data samples and inaccurately labeled disruption precursor samples. We demonstrate the effectiveness and reliability of anomaly detection predictors based on different algorithms on J-TEXT and EAST to evaluate the reliability of the precursor onset time inferred by the anomaly detection predictor. The precursor onset times inferred by these predictors reveal that the labeling methods have room for improvement as the onset times of different shots are not necessarily the same. Finally, we optimize precursor labeling using the onset times inferred by the anomaly detection predictor and test the optimized labels on supervised learning disruption predictors. The results on J-TEXT and EAST show that the models trained on the optimized labels outperform those trained on fixed onset time labels.Comment: 21 pages, 11 figure

Retinal Nerve Fiber Layer Thinning Is Associated With Brain Atrophy: A Longitudinal Study in Nondemented Older Adults

Backgrounds: Abnormal retinal nerve fiber layer (RNFL) thickness has been observed in patients with Alzheimer’s disease (AD) and therefore suggested to be a potential biomarker of AD. However, whether the changes in RNFL thickness are associated with the atrophy of brain structure volumes remains unknown. We, therefore, set out a prospective investigation to determine the association between longitudinal changes of RNFL thickness and brain atrophy in nondemented older participants over a period of 12 months.Materials and Methods: We measured the RNFL thickness using optical coherence tomography (OCT) and brain structure volumes by 3T magnetic resonance imaging (MRI) before and after 12 months. Cognitive function was assessed using the Chinese version of Mini-Mental State Examination (CMMSE) and Repeatable Battery for the Assessment of Neurological Status. Associations among the changes of RNFL, brain structures and cognitive function were analyzed with Spearman correlation and multiple linear regression models adjusting for the confounding factors.Results: Fifty old participants were screened and 40 participants (mean age 71.8 ± 3.9 years, 60% were male) were enrolled at baseline. Among them, 28 participants completed the follow-up assessments. The average reduction of RNFL thickness was inversely associated with the decrease of central cingulate cortex volume after the adjustment of age and total intracranial volume (β = −0.41, P = 0.039). Specifically, the reduction of RNFL thickness in the inferior, not other quadrants, was independently associated with the decline of central cingulate cortex volume after the adjustment (β = −0.52, P = 0.006). Moreover, RNFL thinning, central cingulate cortex atrophy and the aggregation of white matter hyperintensities (WMH) were found associated with episodic memory in these older adults with normal cognition.Conclusions: RNFL thinning was associated with cingulate cortex atrophy and episodic memory decline in old participants. The longitudinal changes of RNFL thickness are suggested to be a useful complementary index of neurocognitive aging or neurodegeneration

Feature-based Transferable Disruption Prediction for future tokamaks using domain adaptation

The high acquisition cost and the significant demand for disruptive discharges for data-driven disruption prediction models in future tokamaks pose an inherent contradiction in disruption prediction research. In this paper, we demonstrated a novel approach to predict disruption in a future tokamak only using a few discharges based on a domain adaptation algorithm called CORAL. It is the first attempt at applying domain adaptation in the disruption prediction task. In this paper, this disruption prediction approach aligns a few data from the future tokamak (target domain) and a large amount of data from the existing tokamak (source domain) to train a machine learning model in the existing tokamak. To simulate the existing and future tokamak case, we selected J-TEXT as the existing tokamak and EAST as the future tokamak. To simulate the lack of disruptive data in future tokamak, we only selected 100 non-disruptive discharges and 10 disruptive discharges from EAST as the target domain training data. We have improved CORAL to make it more suitable for the disruption prediction task, called supervised CORAL. Compared to the model trained by mixing data from the two tokamaks, the supervised CORAL model can enhance the disruption prediction performance for future tokamaks (AUC value from 0.764 to 0.890). Through interpretable analysis, we discovered that using the supervised CORAL enables the transformation of data distribution to be more similar to future tokamak. An assessment method for evaluating whether a model has learned a trend of similar features is designed based on SHAP analysis. It demonstrates that the supervised CORAL model exhibits more similarities to the model trained on large data sizes of EAST. FTDP provides a light, interpretable, and few-data-required way by aligning features to predict disruption using small data sizes from the future tokamak.Comment: 15 pages, 9 figure

Review of CHINARE chemical oceanographic research in the Southern Ocean during 1984–2016

Between 1984 and 2016, China executed 33 Antarctic cruises with the icebreaker R/V Xuelong, which have provided opportunities for Chinese scientists to investigate the status and changes of the Southern Ocean. Research in chemical oceanography constitutes one of the primary missions of the Chinese National Antarctic Research Expedition (CHINARE). This paper reviews nearly 30 years of Chinese Antarctic expeditions, focusing on the major progress achieved in chemical oceanographic research. Specifically, the sea-surface distributions and air–sea fluxes of CO2 and N2O are considered, and the transport, flux, and budget of organic matter are investigated based on isotopes in the Southern Ocean, especially in Prydz Bay. In addition, the nutrient distribution and deep-water particle export in Prydz Bay and the study of aerosol heavy metal characteristics are considered. Finally, the prospects for future Chinese Antarctic chemical oceanographic research are outlined

Critical roles of edge turbulent transport in the formation of high-field-side high-density front and density limit disruption in J-TEXT tokamak

This article presents an in-depth study of the sequence of events leading to density limit disruption in J-TEXT tokamak plasmas, with an emphasis on boudary turbulent transport and the high-field-side high-density (HFSHD) front. These phenomena were extensively investigated by using Langmuir probe and Polarimeter-interferometer diagnostics

Advances in Chinese and international biogeochemistry research in the western Arctic Ocean: a review

Over the past decades, the Arctic Ocean has experienced rapid warming under climate change, which has dramatically altered its physical and biogeochemical properties. Reduction in the sea-ice cover is one of the most important driving forces of biogeochemical changes in the Arctic Ocean. Between 1999 and 2016, seven Chinese National Arctic Research Expeditions have taken place in the Bering and Chukchi seas, allowing assessment of the biogeochemical response of the western Arctic Ocean to global warming. Herein, we summarize advances in Chinese and international marine biogeochemistry research in the western Arctic Ocean, reviewing results from the Chinese expeditions and highlighting future trends of biogeochemistry in the Pacific Arctic region. The findings reported in this paper contribute towards a better understanding of water masses, greenhouse gases, nutrients, ocean acidification, and organic carbon export and burial processes in this region

Validation of the plasma-wall self-organization model for density limit in ECRH-assisted start-up of Ohmic discharges on J-TEXT

A recently developed plasma-wall self-organization (PWSO) model predicts a significantly enhanced density limit, which may be attainable in tokamaks with ECRH-assisted ohmic startup and sufficiently high initial neutral density. Experiments have been conducted on J-TEXT to validate such a density limit scenario based on this model. Experimental results demonstrate that increasing the pre-filled gas pressure or ECRH power during the startup phase can effectively enhance plasma purity and raise the density limit at the flat-top. Despite the dominant carbon fraction in the wall material, some discharges approach the edge of the density-free regime of the 1D model of PWSO.Comment: 17 pages, 8 figure