Functional Coupling of Slack Channels and P2X3 Receptors Contributes to Neuropathic Pain Processing

The sodium-activated potassium channel Slack (K_Na1.1, Slo2.2, or Kcnt1) is highly expressed in populations of sensory neurons, where it mediates the sodium-activated potassium current (I_KNa) and modulates neuronal activity. Previous studies suggest that Slack is involved in the processing of neuropathic pain. However, mechanisms underlying the regulation of Slack activity in this context are poorly understood. Using whole-cell patch-clamp recordings we found that Slack-mediated I_KNa in sensory neurons of mice is reduced after peripheral nerve injury, thereby contributing to neuropathic pain hypersensitivity. Interestingly, Slack is closely associated with ATP-sensitive P2X3 receptors in a population of sensory neurons. In vitro experiments revealed that Slack-mediated I_KNa may be bidirectionally modulated in response to P2X3 activation. Moreover, mice lacking Slack show altered nocifensive responses to P2X3 stimulation. Our study identifies P2X3/Slack signaling as a mechanism contributing to hypersensitivity after peripheral nerve injury and proposes a potential novel strategy for treatment of neuropathic pain.     

Revisiting CO2 emissions convergence in G18 countries

This study revisits whether CO₂ emissions converge in G18 countries over the period of 1950–2013. To work on this empirical analysis, we employ a more powerful quantile unit root test with per capita CO₂ emissions. While conventional unit root tests fail to reject convergence in CO₂ emissions in these G18 countries, quantile unit root test results demonstrate CO₂ emissions converged in 5 of these G18 countries (i.e., Australia, Brazil, Canada, Germany, and India). Our empirical results have important policy implications for the governments of G18 countries to direct efficient and effective energy policies to reduce the CO₂ emissions.     

滚齿工艺对齿根粗糙度的影响

针对国内外风电和工业齿轮箱轻量化的设计趋势,较低的安全系数对齿轮齿根弯曲强度提出了更为严格的要求。研究表明,在材料技术和齿形设计难以再优化的情况下,滚齿加工的粗糙度,尤其是齿根部位的粗糙度对齿轮弯曲强度的影响尤为敏感。针对滚齿工艺过程,从滚齿加工参数、刀具前刀面粗糙度和刀具刃口圆角三方面进行分析,验证其对齿根粗糙度的影响。     

Bootstrap procedures for detecting multiple persistence shifts in heteroskedastic time series

This article proposes new bootstrap procedures for detecting multiple persistence shifts in a time series driven by non-stationary volatility. The assumed volatility process can accommodate discrete breaks, smooth transition variation as well as trending volatility. We develop wild bootstrap sup-Wald tests of the null hypothesis that the process is either stationary [I(0)] or has a unit root [I(1)] throughout the sample. We also propose a sequential procedure to estimate the number of persistence breaks based on ordering the regime-specific bootstrap p-values. The asymptotic validity of the advocated procedures is established both under the null of stability and a variety of persistence change alternatives. A comparison with existing tests that assume homoskedasticity illustrates the finite sample improvements offered by our methods. An application to OECD inflation rates highlights the empirical relevance of the proposed approach and weakens the case for persistence change relative to existing procedures.     

Root cause analysis of the fracture of a sonar window caused by hydrostatic,hydrodynamic, and transient forces around a ship

Sonar systems are installed in naval vessels to inspect objects in the sea. When the system is installed at the bulbous bow of the ship, it can be vulnerable to fractures in rough seas due to hydrostatic and hydrodynamic forces, such as fluid-induced forces, and transient forces, such as slamming and collision with submerged foreign objects. In this paper, root causes analysis (RCA) of the fracture of a sonar window of a typical naval vessel was performed. To identify the root causes of the fracture, a numerical analysis was performed of the stress distribution on a sonar window under various extreme conditions. The results of the analysis, together with hypotheses of the causes of the fracture, are presented. The results of the analysis were verified by measuring the stress on the sonar window under typical sailing conditions of ships. The RCA demonstrated that buckling in response to the hydrostatic forces applied under the typical operating conditions of a water management system (WMS), in addition to excessive slamming, can cause a sonar window to fracture. Based on this RCA, corrective actions to prevent sonar window fractures include changing the material of the window and the operating conditions of the WMS.     

Deterministic and probabilistic ship pitch prediction using a multi-predictor integration model based on hybrid data preprocessing,reinforcement learning and improved QRNN

The deterministic and probabilistic prediction of ship motion is important for safe navigation and stable real-time operational control of ships at sea. However, the volatility and randomness of ship motion, the non-adaptive nature of single predictors and the poor coverage of quantile regression pose serious challenges to uncertainty prediction, making research in this field limited. In this paper, a multi-predictor integration model based on hybrid data preprocessing, reinforcement learning and improved quantile regression neural network (QRNN) is proposed to explore the deterministic and probabilistic prediction of ship pitch motion. To validate the performance of the proposed multi-predictor integrated prediction model, an experimental study is conducted with three sets of actual ship longitudinal motions during sea trials in the South China Sea. The experimental results indicate that the root mean square errors (RMSEs) of the proposed model of deterministic prediction are 0.0254°, 0.0359°, and 0.0188°, respectively. Taking series #2 as an example, the prediction interval coverage probabilities (PICPs) of the proposed model of probability predictions at 90%, 95%, and 99% confidence levels (CLs) are 0.9400, 0.9800, and 1.0000, respectively. This study signifies that the proposed model can provide trusted deterministic predictions and can effectively quantify the uncertainty of ship pitch motion, which has the potential to provide practical support for ship early warning systems.