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Over the decades, testing gravitational red-shift (GRS) based on microwave links has made great process, including the GPA experiment, the planned Atomic Clock Ensemble in Space mission, and the China Space Station (CSS). Until now, the formulations of microwave links are almost all based on the time comparison. However, there are advantages of using frequency comparison instead of time comparison to test GRS. Here we develop a tri-frequency combination method based on the measurements of the frequency shifts of three independent microwave links between a space station and a ground station. Aiming at the frequency links’ accuracy of $$3\times 10^{-16}$$ 3 × 10 - 16 , we should consider various effects, including the Doppler effect, second-order Doppler effect, atmospheric frequency shift, tidal effects, refraction caused by the atmosphere, and Shapiro effect, with accuracy levels of tens of centimeters. The CSS will complete construction in 2022, and the formulation proposed in this study will enable us to test GRS at an accuracy level of at least $$2\times 10^{-6}$$ 2 × 10 - 6 , which is one order higher than the present accuracy level of $$7\times 10^{-5}$$ 7 × 10 - 5 .

Background. Anion gap (AG) has been proved to be associated with prognosis of many cardiovascular diseases. This study is aimed at exploring the association of AG with inhospital all-cause mortality and adverse clinical outcomes in coronary care unit (CCU) patients. Method. All data of this study was extracted from Medical Information Mart for Intensive Care III (MIMIC-III, version 1.4) database. All patients were divided into four groups according to AG quartiles. Primary outcome was inhospital all-cause mortality. Lowess smoothing curve was drawn to describe the overall trend of inhospital mortality. Binary logistic regression analysis was performed to determine the independent effect of AG on inhospital mortality. Result. A total of 3593 patients were enrolled in this study. In unadjusted model, as AG quartiles increased, inhospital mortality increased significantly, OR increased stepwise from quartile 2 (OR, 95% CI: 1.01, 0.74-1.38, P=0.958) to quartile 4 (OR, 95% CI: 2.72, 2.08-3.55, P<0.001). After adjusting for possible confounding variables, this association was attenuated, but still remained statistically significant (quartile 1 vs. quartile 4: OR, 95% CI: 1.02, 0.72-1.45 vs. 1.49, 1.07-2.09, P=0.019). Moreover, CCU mortality (P<0.001) and rate of acute kidney injury (P<0.001) were proved to be higher in the highest AG quartiles. Length of CCU (P<0.001) and hospital stay (P<0.001) prolonged significantly in higher AG quartiles. Maximum sequential organ failure assessment score (SOFA) (P<0.001) and simplified acute physiology score II (SAPSII) (P<0.001) increased significantly as AG quartiles increased. Moderate predictive ability of AG on inhospital (AUC: 0.6291), CCU mortality (AUC: 0.6355), and acute kidney injury (AUC: 0.6096) was confirmed. The interactions were proved to be significant in hypercholesterolemia, congestive heart failure, chronic lung disease, respiratory failure, oral anticoagulants, Beta-blocks, angiotensin-converting enzyme inhibitor (ACEI)/angiotensin receptor blocker (ARB), and vasopressin treatment subgroups. Conclusion. AG was an independent risk factor of inhospital all-cause mortality and was associated with adverse clinical outcomes in CCU patients.

According to general relativity theory (GRT), the clock at a position with lower geopotential ticks slower than an identical one at a position with higher geopotential. Here, we provide a geopotential comparison using a non-transportable hydrogen clock and a transportable hydrogen clock for altitude transmission based on the two-way satellite time and frequency transfer (TWSTFT) technique. First, we set one hydrogen clock on the fifth floor and another hydrogen clock on the ground floor, with their height difference of 22.8 m measured by tape, and compared the time difference between these two clocks by TWSTFT for 13 days. Then, we set both clocks on the ground floor and compared the time difference between the two clocks for 7 days for zero-baseline calibration (synchronization). Based on the measured time difference between the two clocks at different floors, we obtained the height difference of $28 \pm 05.4$ m, which coincides well with the tape-measured result. This experiment provides a method of height propagation using precise clocks based on the TWSTFT technique., 19 pages, 6 figures

Previously, we demonstrated that Schisandrol B (SolB) protected against lithocholic acid (LCA)-induced cholestatic liver injury (CLI) through pregnane X receptor (PXR). Additionally, growing evidence has revealed that pyroptosis is involved in CLI. Whether the hepatoprotective effect of SolB driven by PXR activation is related to pyroptosis in CLI remains unclear. First, the hepatoprotective effect of SolB was confirmed, as evidenced by the decreased mortality, morphological and histopathological changes, and biochemical parameters. The upregulated serum lactic dehydrogenase (LDH) level, increased number of TUNEL-positive cells, and formation of hepatocyte membrane pores induced by LCA were significantly alleviated after SolB pretreatment, indicating that SolB attenuated LCA-induced hepatocyte damage. Further analysis revealed that both NOD-like receptor protein 3 (NLRP3) inflammasome-induced canonical pyroptosis and apoptosis protease activating factor-1 (Apaf-1) pyroptosome-induced noncanonical pyroptosis were significantly inhibited after SolB pretreatment, as illustrated by the decreased expression levels of NLRP3, ASC, caspase-1, and GSDMD and the levels of Apaf-1, caspase-11 p20, caspase-3 p20, and GSDME. Furthermore, the activation of the NF-κB and FoxO1 signaling pathways was inhibited after SolB pretreatment. In addition, the activation of PXR via SolB was proven by luciferase reporter gene assays and the upregulation of PXR targets. The results illustrated that SolB could significantly inhibit NLRP3 inflammasome-induced canonical pyroptosis through the PXR/NF-κB/NLRP3 axis and inhibit Apaf-1 pyroptosome-induced noncanonical pyroptosis through the PXR/FoxO1/Apaf-1 axis. Collectively, this study revealed that SolB protected against CLI by inhibiting pyroptosis through PXR, providing new insights for understanding the molecular mechanism of SolB as a promising anti-cholestatic agent.

The astrocytes-secreted active molecule, Hevin considerably contributes in the transsynaptic bridge of neurexin1β/neuligin1 in excitatory synapse. Previous studies have demonstrated that activity-dependent synaptic recruitment of spinal neuroligin1 and GluA1-containing AMPA receptors (AMPARs) is involved in incisional, inflammatory and neuropathic pain. Here, we hypothesized that Hevin induced postoperative pain hypersensitivity by enhancing the neurexin1β/neuroligin1-mediated synaptic targeting of GluA1-containing AMPARs in spinal dorsal horns (DH). Our results showed that plantar incision induced significant postoperative pain behavior, which was described by the cumulative pain scores. At 1 d and 3 d post-incision, Hevin expression was considerably elevated in ipsilateral DHs, although it recovered to baseline value at 5 d following the incision. At 1 d post plantar incision, the neurexin1β/neuroligin1 interactions significantly increased in ipsilateral DHs in rats subjected to incision when compared with those in control rats. Intrathecal pretreatments of small interference RNA targeting Hevin substantially suppressed postoperative pain hypersensitivity and reduced the neurexin1β/neurolgin1 interaction as well as the synaptic targeting of GluA1 in ipsilateral spinal DHs. These data suggest that Hevin induced postoperative pain hypersensitivity by enhancing the neurexin1β/neuroligin1 interaction and subsequent synaptic targeting of GluA1-containing AMPARs in ipsilateral spinal DHs. It provides new insights into the role of Hevin-mediated trans-synaptic regulation in postoperative pain hypersensitivity, which would help develop a novel therapeutic strategy.

Background: Neutrophil percentage to albumin ratio (NPAR) was proved to be correlated with the prognosis of a variety of diseases. The purpose of this study was to explore the effect of NPAR on the prognosis of coronary care unit (CCU) dpatients.Method: All data of this study was extracted from Medical Information Mart for Intensive Care III (MIMIC-III, version1.4) database. All patients were divided into four groups according to NPAR quartiles. Primary outcome was in-hospital mortality and secondary outcomes were 30-day mortality, 365-day mortality, length of CCU stay, length of hospital stay, acute kidney injury, renal replacement therapy. Multivariable binary logistic regression analysis was performed to confirm the independent effect of NPAR. Subgroup analysis was used to determine the effect of NPAR on in-hospital mortality in different subgroups. Receiver-operating characteristic (ROC) curves were applied to evaluate the ability of NPAR to predict in-hospital mortality. Kaplan–Meier curves were built to compare cumulative survival of different groups.Result: 2364 CCU patients were enrolled in this study. In-hospital mortality rate increased significantly as NPAR quartiles increased (P < 0.001). In multivariable logistic regression, NPAR was proved to be independently associated with in-hospital mortality (Quartile 4 vs Quartile 1: OR, 95% CI: 1.80, 1.19-2.72, P=0.005, P for trend = 0.001). Moderate ability of NPAR to predict in-hospital mortality was demonstrated through ROC curves, the AUC of NPAR was 0.653 (PConclusion: NPAR was an independent risk factor of in-hospital mortality in CCU patients and had a moderate ability to predict in-hospital mortality.

Due to the influence of pseudo-range noise, traditional GNSS common view method is difficult to improve the accuracy of time-frequency transfer. GNSS carrier phase precise point positioning (PPP) time-frequency transfer has become a research hotspot because of its high accuracy. In this paper, a time-frequency transfer model of GNSS carrier phase single difference (SD) and Integer Single Difference (ISD) between any two ground stations is studied. In order to solve the problem that the SD ambiguity cannot be fixed due to the influence of the phase biases at the receivers, a method of SD ambiguity fixing is proposed, that is the SD ambiguity is fixed with the constraint of the fixed double difference ambiguity among several stations and satellites. Here taking four time-frequency links between pairs of ground stations, BRUX-OPMT (262.3km), BRUX-PTBB (454.6km), BRUX-WTZR (637.7km) and BRUX-CEBR (1331.6km) as examples, the multi-GNSS time-frequency transfer experiment of SD, ISD and PPP method is carried out. The results show that the SD and PPP time-frequency transfer accuracy is equivalent, the stability of ISD is improved compared with SD, and the difference RMS between epochs is less than 10 ps. High precision carrier phase SD, ISD and PPP technology can be applied to the study of determining the gravity potential based on time-frequency measurements. This study is supported by the National Natural Science Foundations of China (NSFC) under Grants 42030105, 41721003, 41804012, 41631072, 41874023, Space Station Project (2020)228, and the Natural Science Foundation of Hubei Province of China under Grant 2019CFB611.

The quick development of the global navigation satellite system (GNSS) time transfer technique provides a good opportunity to determine the geopotential difference based on the general relativity theory (GRT). In this study, we propose an approach that uses the precise point positioning (PPP) technique to directly compute clock offsets between two clocks at two arbitrary positions for the purpose of determining the geopotential difference and the accuracy of this approach depends not only on both the accuracies and stabilities of clocks, but also the time transfer technique itself. To validate the relationship between the performance of GNSS time transfer and the accuracy of this approach, simulation experiments are conducted. We evaluated the performances of GNSS time transfer in different cases using different type of free-running clocks, and results show that the proposed approach could be applied to testing GRT. This study was supported by the National Natural Science Foundations of China (grant Nos. 41721003, 42030105, 41804012, 41631072, 41874023, 41574007), Natural Science Foundation of Hubei Province of China (grant Nos. 2019CFB611), and Space Station Project (2020)228.

Background. Neutrophil percentage-to-albumin ratio (NPAR) has been proved to be associated with clinical outcome of many diseases. This study was aimed at exploring the independent effect of NPAR on all-cause mortality of critically ill patients with coronary artery disease (CAD). Method. NPAR was calculated as neutrophil percentage numerator divided by serum albumin concentration. Clinical endpoints were 30-day, 90-day, and 365-day all-cause mortality. Multivariable Cox proportional hazard models were performed to confirm the association between NPAR and all-cause mortality. Result. 3106 patients with CAD were enrolled. All-cause mortality rates of 30 days (P<0.001), 90 days (P<0.001), and 365 days (P<0.001) increased as NPAR tertiles increased. And after adjusting for possible confounding variables, NPAR was still independently associated with 30-day (third tertile group versus first tertile group: HR, 95% CI: 1.924, 1.471-2.516; P for trend < 0.001), 90-day (third tertile group versus first tertile group: HR, 95% CI: 2.053, 1.646-2.560; P for trend < 0.001), and 365-day (third tertile group versus first tertile group: HR, 95% CI: 2.063, 1.717-2.480; P for trend < 0.001) all-cause mortality in patients with CAD. Subgroup analysis did not find obvious interaction in most subgroups. Conclusion. NPAR was independently correlated with 30-day, 60-day, and 365-day all-cause mortality in critically ill patients with CAD.

Abstract In this study, we carried out experiments of the geopotential difference determination at CASIC, Beijing with the help of two hydrogen atomic clocks, using the two-way satellite time and frequency transfe technique. Here the ensemble empirical mode decomposition method is adopted to extract geopotential-related time-elapse signals from the original observations. The clock-comparison-determined geopotential difference in the experiments is determined, which is compared to the previously known results determined by conventional approach. Results show that the geopotential difference determined by time comparison deviates from that determined by conventional approach by about 1589 m2s-2, which is equivalent to 162 m in height, in consistence with the stability of the hydrogen atomic clocks applied in the experiments (at the level of 10-15/day). Since the stability of the optical clocks achieve 10-18 level, the geopotential determination by accurate clocks is prospective, and it is prospective to realize the unification of the world vertical height system. This study is supported by NSFCs (grant Nos. 41721003, 41631072, 41874023, 41804012, 41429401, 41574007) and Natural Science Foundation of Hubei Province of China (grant No. 2019CFB611).

Atomic Clock Ensemble in Space (ACES) is an ESA mission designed mainly to test gravitational redshift with high-performance atomic clocks in space and on the ground. Here we develop tri-frequency combination (TFC) method based on the measurements of frequency shifts of three independent microwave links between ACES and a ground station. The potential scientific object requires an accuracy of at least 3×10-16, thus we need to consider various effects including Doppler effect, second-order Doppler effect, atmospheric frequency shift, tidal effects, refraction caused by atmosphere, Shapiro effect, with accuracy level of tens of centimeters. The ACES payload will be launched in middle of 2021, and the formulation proposed in this study will enable us to test gravitational redshift at an accuracy level at least 2×10-6 level, one order more higher than the present accuracy level. This study is supported by NSFCs (grant Nos. 41721003, 41631072, 41874023, 41804012, 41429401, 41574007) and Natural Science Foundation of Hubei Province of China (grant No. 2019CFB611).

According to general relativity theory, one may determine the geopotential difference between two arbitrary stations by comparing there-located clocks’ running rates. In this study, we provide experimental results of the geopotential determination based on the time elapse comparison between two hydrogen atomic clocks, one fixed clock and one portable clock , using the common view satellite time transfer (CVSTT) technique. We compared the portable clock located at Jiugongshan Time Frequency Station (JTFS) with the fixed clock located at Luojiashan Time Frequency Station (LTFS) for 30 days. The two stations are separated by a geographic distance of around 240 km with height difference around 1230 m. Then the clock was transported (without stopping its running status) to LTFS and compared with clock for zero-baseline calibration for 15 days. The clock-comparison-determined geopotential difference between JTFS and LTFS is determined. Results show that the clock-comparison-determined result deviates from the EGM20080-determined result by about 2322±1609 m2s-2, equivalent to 237±164 m in height, in consistence with the stability of the hydrogen atomic clocks applied in the experiments (at the level of 10-15/day).This study is supported by NSFCs (grant Nos. 41721003, 41631072, 41874023, 41804012, 41429401, 41574007) and Natural Science Foundation of Hubei Province of China (grant No. 2019CFB611).

Klobuchar model can reflect the spatial and temporal variations of ionospheric feature, but model fixed initial phase and night-time delay will introduce a large number of errors. Aiming at the shortcomings of the models, take least-squares surface fitting model as the background, using CORS network in Nanning region to measure the data correctly, the Klobuchar model's initial phase, amplitude, and night-time delay values are steadily corrected, so as to establish regional ionospheric model in Nanning, the results show that the accuracy of Klobuchar model is improved significantly.

The formation of the ionosphere is mainly the interaction of solar radiation and the earth's atmosphere, in different temporal-spatial environment, the characteristics of the ionosphere is more complex, and the Total Electron Content (TEC) is one of the important parameters of the ionospheric morphology and structure. Therefore, in this paper, using the high-precision TEC time series provided by the International GNSS Service (IGS) as experimental data, by Fast Fourier Transform (FFT) to detect its periodic changes, and then focus on analysis the characteristics of diurnal variation, seasonal variation and annual variation and winter anomaly, simultaneous analysis of the ionospheric characteristics vary with latitude and longitude. The result show that: (1) TEC changes more intense during the day, but the night is quiet, and in different latitudes, the TEC reached peak value at different moment; (2) Winter anomaly exists only during the day, night does not exist; (3) In the same time domain, TEC value decreases gradually with the increase of latitude, and it has different spatial variation features in different hemispheres.

Aiming at the characteristic of nonlinear and non-stationary in ionospheric total electron content(TEC), this article bring Wavelet Analysis into the autoregressive integrated moving average model to forecast the next four days’ TEC values by using six days’ ionospheric grid observation data of Chinese area in 2010 provided by IGS station. Taking IGS station’s observation data as true value, compare the forecast value with it then count the forecast accuracies which are to prove that it has a quite good result by using WARIMA model to forecast Chinese area’s Ionospheric grid data. But near the geomagnetic latitude of about ±20°grid, the model’s forecast results are a little worse than others’ because Geomagnetic activity is irregular which lead to the TEC values there change greatly.

As the fact that most of the ground-based GPS lacks of the detection of the upper-air meteorological data, thus the application of ground-based GPS sensing of water vapor technology has been limited due to the inaccurately calculated weighted mean temperature. In that case, this paper has studied and analyzed the methods of obtaining weighted mean temperature by deriving the data from GGOS Atmosphere weighted mean temperature grid data in Xinjiang. By using the radiosonde data, this paper has evaluated the accuracy of the weighted mean temperature(GTm) derived from GGOS atmosphere weighted mean temperature grid data and considering the seasonal and geographic factors , we employed a correction model to fit the residuals of GTm. Results show that the GTm derived from mean value interpolation and corrected by correction model meet the requirements of ground-based GPS precision sensing of Water Vapor in Xinjiang ; The inner average precision RMSD is 2.33K , MAE is 1.80 K; The outer average precision RMSD is 2.36K , MAE is 1.85 K.

This paper investigates the comparative performance of several information-driven search strategies and decision rules using a canonical target classification problem. Five sensor models are considered: one obtained from classical estimation theory and four obtained from Bernoulli, Poisson, binomial, and mixture-of-binomial distributions. A systematic approach is presented for deriving information functions that represent the expected utility of future sensor measurements from mutual information, Renyi divergence, Kullback-Leibler divergence, information potential, quadratic entropy, and the Cauchy-Schwarz distance. The resulting information-driven strategies are compared to direct-search, alert-confirm, task-driven (TS), and log-likelihood-ratio (LLR) search strategies. Extensive numerical simulations show that quadratic entropy typically leads to the most effective search strategy with respect to correct-classification rates. In the presence of prior information, the quadratic-entropy-driven strategy also displays the lowest rate of false alarms. However, when prior information is absent or very noisy, TS and LLR strategies achieve the lowest false-alarm rates for the Bernoulli, mixture-of-binomial, and classical sensor models.

A methodology is developed for planning the sensing strategy of a robotic sensor deployed for the purpose of classifying multiple fixed targets located in an obstacle-populated workspace. Existing path planning techniques are not directly applicable to robots whose primary objective is to gather sensor measurements using a bounded field of view (FOV). This paper develops a novel approximate cell-decomposition method in which obstacles, targets, sensor's platform, and FOV are represented as closed and bounded subsets of an Euclidean workspace. The method constructs a connectivity graph with observation cells that is pruned and transformed into a decision tree from which an optimal sensing strategy can be computed. The effectiveness of the optimal sensing strategies obtained by this methodology is demonstrated through a mine-hunting application. Numerical experiments show that these strategies outperform shortest path, complete coverage, random, and grid search strategies, and are applicable to nonoverpass capable robots that must avoid targets as well as obstacles.

Control and optimization of acoustic sensors can significantly impact the effectiveness of sonar deployment in variable and uncertain underwater environments. On the other hand, the design of optimal control systems requires tractable models of system dynamics, which in this case include acoustic-wave propagation phenomena. High-fidelity acoustic models that capture the influence of environmental conditions on wave propagation involve partial differential equations (PDEs), and are computationally intensive. Also, by relying on the numerical solution of PDEs for given boundary and initial conditions, they do not provide closed-form functional forms for the propagation loss or other output variables. In this paper, a simple Bayesian network (BN) model of acoustic propagation is presented for use in sonar control. The performance of the BN model compares favorably to that of a radial basis function neural network. Additionally, the sensor range dependency on spatial and temporal coordinates can be estimated and utilized to compute optimal sonar control strategies.

The paper presents a three-layer feedforward backpropagation (BP) artificial neural network (ANN), whose output is battery state-of-charge (SOC), to estimate and predict SOC of high power Ni-MH rechargeable battery. Five ANN inputs are novelly selected to improve the accuracy of ANN prediction by the proposed method of correlation coefficient ranking based on correlation analysis of different variables and SOC, and they are: battery discharging current i, accumulated ampere hours Ah, battery terminal voltage v, time-average terminal voltage tav and twice time-average voltage ttav (i.e. time-average of tav). Meanwhile, six training sets are equally selected from thirteen data sets about constant current discharging (CCD) from 100 % to 0 % SOC and Levenberg-Marquardt training algorithm is selected. Comparisons between simulation and measurement verify the proposed ANN model. Especially, the ANN can satisfyingly estimate SOC of battery (pack) whose starting SOC (i.e. SOC/sub 0/) is not originally known after about ten minutes (short time compared with the whole discharging process) constant load discharging (CLD), and most of absolute values of absolute errors are not more than 5 %.

Mobile robot often relies on a battery system as its power supply and such kind of mobile robot is called cableless mobile robot. In the past years, while there are many researches on automation and control techniques, mechanical and sensor designs of mobile robot, very little systematic and comprehensive work has been done in the design of rechargeable battery power system for cableless mobile robot. This paper discusses the above problem from three different aspects: selection of rechargeable battery type, battery management technique and energy renewal. In the section on selection of rechargeable battery, many different types of traction rechargeable battery are introduced and the factors that are crucial for cableless mobile robot applications are compared. The section on battery management technique focuses on battery state-of-charge (SOC) estimation. In the section on energy renewal, two typical charging techniques, conductive charging and inductive charging are discussed. In the final section, one implementation example, high power Ni-MH rechargeable battery system for TH-1 humanoid robot which is being developed by Tsinghua University, is introduced.

Battery is a quite complex and nonlinear system comprised of interacting physical and chemical processes, although it may seem deceptively simple. For this reason, existing battery models are either partially successful or too complicated and inconvenient in modeling and simulation applications. This paper presents a dynamic neural network model with time-delayed system output feedback for modelling and identification of a Ni-MH battery during discharging. Comparisons between the simulation and measurement verify the presented model. Compared with the methods based on the Peukert equation, which is often used for the calculation of the available capacity and simulation of battery discharging curves, the ANN method is more accurate.