Identifying Strongly Lensed Gravitational Waves with the Third-generation Detectors

The joint detection of GW signals by a network of instruments will increase the detecting ability of faint and far GW signals with higher signal-to-noise ratios (SNRs), which could improve the ability of detecting the lensed GWs as well, especially for the 3rd generation detectors, e.g. Einstein Telescope (ET) and Cosmic Explorer (CE). However, identifying Strongly Lensed Gravitational Waves (SLGWs) is still challenging. We focus on the identification ability of 3G detectors in this article. We predict and analyze the SNR distribution of SLGW signals and prove only 50.6\% of SLGW pairs detected by ET alone can be identified by Lens Bayes factor (LBF), which is a popular method at present to identify SLGWs. For SLGW pairs detected by CE\&ET network, owing to the superior spatial resolution, this number rises to 87.3\%. Moreover, we get an approximate analytical relation between SNR and LBF. We give clear SNR limits to identify SLGWs and estimate the expected yearly detection rates of galaxy-scale lensed GWs that can get identified with 3G detector network.Comment: 9 pages, 7 figure

The effect of ginger supplementation on serum C-reactive protein, lipid profile and glycaemia: a systematic review and meta-analysis

Aim: To undertake a systematic review and meta-analysis of prospective studies to determine the effect of ginger supplementation on serum C-reactive protein (CRP), lipid profile, and glycaemia. Method: PubMed-MEDLINE, Web of Science, Cochrane Database, and Google Scholar databases were searched (up until July 2016) to identify prospective studies evaluating the impact of ginger supplementation on serum CRP. Random-effects model meta-analysis was used for quantitative data synthesis. Sensitivity analysis was conducted using the leave-one-out method. Heterogeneity was quantitatively assessed using the I2 index. Systematic review registration: CRD42016035973. Results: From a total of 265 entries identified via searches, 9 studies were included in the final selection. The meta-analysis indicated a significant reduction in serum CRP concentrations following ginger supplementation [weighted mean difference (WMD)-0.84 mg/L (95% CI -1.38 to -0.31, I2 56.3%)]. The WMD for fasting blood glucose and HbA1c was -1.35 mg/dl (95% CI -2.04 to -0.58, I2 12.1%) and -1.01 (95% CI -1.28 to -0.72, I2 9.4%), respectively. Moreover, high-density lipoprotein and triglyceride significantly improved after ginger administration [1.16 mg/dl (95% CI 0.52 to 1.08, I2 12.3%) and -1.63 mg/dl (95% CI -3.10 to -0.17, I2 8.1%), respectively]. These findings were robust in sensitivity analyses. Random-effects meta-regression revealed that changes in serum CRP levels were independent of the dosage of ginger supplementation (slope -0.20; 95% CI -0.95 to 0.55; p=0.60). Conclusions: This meta-analysis suggests that ginger supplementation significantly reduces serum CRP and improves glycaemia indexes and lipid profile. Randomized control trials with larger sample size and with a longer-term follow-up period should be considered for future investigations

Yiguanjian cataplasm attenuates opioid dependence in a mouse model of naloxone-induced opioid withdrawal syndrome

AbstractObjectiveTo investigate the effect of Yiguanjian (YGJ) cataplasm on the development of opioid dependence in a mouse model of naloxone-induced opioid withdrawal syndrome.MethodsOne hundred Swiss albino mice, of equal male to female ratio, were randomly and equally divided into 10 groups. A portion (3 cm2) of the backside hair of the mice was removed 1 day prior to the experiment. Morphine (5 mg/kg) was intraperitoneally administered twice daily for 5 days. YGJ cataplasm was prepared and pasted on the bare region of the mice immediately before morphine administration on day 3 and subsequently removed at the end day 5. On day 6, naloxone (8 mg/kg) was intraperitoneally injected to precipitate opioid withdrawal syndrome. Behavioral observation was performed in two 30-min phases immediately after naloxone injection.ResultsThe YGJ cataplasm significantly and dose-dependently attenuated morphine-naloxone-induced experimental opioid withdrawal, in terms of withdrawal severity score and the frequencies of jumping, rearing, forepaw licking, and circling behaviors. However, YGJ cataplasm treatment did not alter the acute analgesic effect of morphine.ConclusionYGJ cataplasm could attenuate opioid dependence and its associated withdrawal symptoms. Therefore, YGJ cataplasm could serve as a potential therapy for opioid addiction in the future

Food Patterns are Associated with Likelihood of CKD in US Adults

We investigated the association between dietary patterns and prevalent chronic kidney diseases (CKD), in participants of the 2005-2012 US National Health and Nutrition Examination Survey (NHANES) conducted between 2005 and 2012, who had measured data on dietary intake and kidney function. Analyse of covariance (ANCOVA) and logistic regression models were employed to account for the survey design and sample weights. A total of 21,649 eligible participants (634 with and 20,015 without prevalent CKD) were included in the final analysis. Three food patterns together explained 50.8% of the variance of the dietary nutrients consumption. The first food pattern was representative of a diet containing high levels of saturated and mono-unsaturated fatty acids; the second food pattern comprised vitamins and trace elements; and the third food pattern was mainly representative of polyunsaturated fatty acids. The odd of prevalent CKD decreased across increasing quarters of vitamins and trace elements, so that the top quarter was associated with a 53% (95%CI: 42-62%) lower odds of CKD in age, sex and race adjusted logistic regression models. These results suggest that vitamins and trace elements intake are associated with lower risk of prevalent CKD

Interferences effects in polarized nonlinear Breit-Wheeler process

The creation of polarized electron-positron pairs by the nonlinear Breit-Wheeler process in short laser pulses is investigated using the Baier-Katkov semiclassical method beyond local-constant-field approximation (LCFA), which allows for identifying the interferences effects in the positron polarization. When the laser intensity is in the intermediate %multiphoton regime, the interferences of pair production in different formation lengths induce an enhancement of pair production probability for spin-down positrons, which significantly affects the polarization of created positrons. The polarization features are distinct from that obtained with LCFA, revealing the invalidity of LCFA in this regime. Meanwhile, the angular distribution for different spin states varies, resulting in an angular-dependent polarization of positrons. The average polarization of positrons at beam center is highly sensitive to the laser's carrier-envelope phase (CEP), which provides a potential alternative way of determining the CEP of strong lasers. The verification of the observed interference phenomenon is possible for the upcoming experiments

The relationship of plasma Trans fatty acids with dietary inflammatory index among US adults

BACKGROUND: It has been suggested that trans fatty acids (TFAs) play an important role in cardiovascular diseases. We investigated the association between plasma TFAs and the dietary inflammatory index (DII) ™ in US adults. METHODS: National Health and Nutrition Examination Survey (NHANES) participants with data on plasma TFAs measured from 1999 to 2010 were included. Energy-adjusted-DII ™ (E-DII ™) expressed per 1000 kcal was calculated from 24-h dietary recalls. All statistical analyses accounted for the survey design and sample weights. RESULTS: Of the 5446 eligible participants, 46.8% (n = 2550) were men. The mean age of the population was 47.1 years overall, 47.8 years for men and 46.5 years for women (p = 0.09). After adjustment for C-reactive protein, body-mass-index, smoking, race, age, education, and marital status in linear regressions, trans 9-hexadecenoic acid [β coefficient 0.068 (95% CI: 0.032 to 0.188)], trans 11-octadecenoic acid [β coefficient 0.143 (95% CI: 0.155 to 0.310)], trans 9-octadecenoic acid [β coefficient 0.122 (95% CI: 0.120 to 0.277)], trans 9, and trans 12-octadienoic acid [β coefficient 0.103 (95% CI: 0.090 to 0.247)] were positively associated with the DII (all p < 0.001). CONCLUSION: The association of plasma TFAs with a marker of dietary inflammation suggests an underlying mechanism in the initiation and progression of cardiovascular diseases

Physics-informed machine learning for understanding rock moisture dynamics in a sandstone cave

Rock moisture, which is a hidden component of the terrestrial hydrological cycle, has received little attention. In this study, frequency domain reflectometry is used to monitor fluctuating rock water content (RWC) in a sandstone cave of the Yungang Grottoes, China. We identified two major cycles of rock moisture addition and depletion, one in summer affected by air vapour concentration and the other in winter caused by freezing-thawing. For the summer-time RWC, by using the long short-term memory (LSTM) network and the SHapley Additive exPlanations (SHAP) method, we find relative humidity, air temperature and wall temperature have contributions to rock moisture, and there is a good match between predicted and measured RWC using the three variables as model inputs. Moreover, by using summer-time vapour concentration and the difference between dew point temperature and wall temperature as input variables of the LSTM network, which belongs to physics-informed machine learning, the predicted RWC has a better agreement with the measured RWC, with increased Nash-Sutcliffe efficiency (NSE) and decreased mean absolute error (MAE) and root mean square error (RMSE). After identifying the causal factors of RWC fluctuations, we also identified the mechanism controlling the inter-day fluctuations of vapour condensation. The increased vapour concentration accompanying a precipitation event leads to transport of water vapour into rock pores, which is subsequently adsorbed onto the surface of rock pores and then condensed into liquid water. With the aid of the physics-informed deep learning model, this study increases understanding of sources of water in caves, which would contribute to future strategies of alleviating weathering in caves.</p

DRNN-based shift decision for automatic transmission

In research on intelligent shift for automatic transmission, the neural network selected has no feedback and lacks an associative memory function. Thus, its adaptability needs to be improved. To achieve this, an automatic shift strategy based on a deep recurrent neural network (DRNN) is proposed. First, a neural network framework was designed in combination with an eight-speed gearbox that matches a particular type of vehicle. Then, the working principle of the DRNN was applied to the shifting process of an automatic gearbox, and the implementation model of the shift logic was established in MATLAB/Stateflow. A data sample obtained from the model was used to train the DRNN. Training and evaluation of the DRNN were accomplished in Python. Finally, a simulation comparison of the DRNN with a back-propagation (BP) neural network proved that after the epochs have been increased, the DRNN has higher precision and adaptation than a BP neural network. This research provides a theoretical basis and technical support for intelligent control of automatic transmission.https://doi.org/10.1177/168781402097529