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Mediation analysis studies situations where an exposure may affect an outcome both directly and indirectly through intervening variables called mediators. It is frequently of interest to test for the effect of the exposure on the outcome, and the standard approach is simply to regress the latter on the former. However, it seems plausible that a more powerful test statistic could be achieved by also incorporating the mediators. This would be useful in cases where the exposure effect size might be small, which for example is common in genomics applications. Previous work has shown that this is indeed possible under complete mediation, where there is no direct effect. In most applications, however, the direct effect is likely nonzero. In this paper we study linear mediation models and find that under certain conditions, power gain is still possible under this incomplete mediation setting for testing the null hypothesis that there is neither a direct nor an indirect effect. We study a class of procedures that can achieve this performance and develop their application to both low- and high-dimensional mediators. We then illustrate their performances in simulations as well as in an analysis using DNA methylation mediators to study the effect of cigarette smoking on gene expression. [ABSTRACT FROM AUTHOR]

In the process of open-pit coal mine production, mining and transport loss of excavator accessories, iron and other large ferromagnetic objects with the coal into the crusher, will result in crusher jammed, broken tooth damage and even motor burn down and other serious production accidents, based on the principle of low frequency eddy current detection can effectively detect ferromagnetic objects, the characteristics of the ferromagnetic objects open-pit mine secondary crushing plant movement monitoring research. Taking SANDVIK's CR610/14—35 double-tooth roller sieve crusher as the experimental object, the mechanism of the detection system was analytically modeled according to the principle of electromagnetic mutual induction. The results of modeling and experiments show that the eddy current generated by ferromagnetic objects is weak due to the existence of strong background noise. The signal to noise ratio(SNR)can be improved by optimizing the parameters of the detector and planning the path of the detector. According to the characteristics of the experimental object, the maximum SNR was obtained when the ratio of the radius of the metal to the detection distance was 0.048, and the ratio of the coil radius to the detection distance was 0.044 5. In the 1~35 kHz segment, the SNR is higher in the low frequency band than the high frequency band. The initial value and response time of the path entering the detection area perpendicular to the detection axis have obvious advantages over the path entering the detection area parallel to the axis.

Biomarkers are often measured in bulk to diagnose patients, monitor patient conditions, and research novel drug pathways. The measurement of these biomarkers often suffers from detection limits that result in missing and untrustworthy measurements. Frequently, missing biomarkers are imputed so that down‐stream analysis can be conducted with modern statistical methods that cannot normally handle data subject to informative censoring. This work develops an empirical Bayes g$$ g $$‐modeling method for imputing and denoising biomarker measurements. We establish superior estimation properties compared to popular methods in simulations and with real data, providing the useful biomarker measurement estimations for down‐stream analysis. [ABSTRACT FROM AUTHOR]

The primary function of a mine hoist is the transportation of personnel and equipment, serving as a crucial link between underground and surface systems. The proper functioning of key components such as work braking and safety braking is essential for ensuring the safety of both personnel and equipment, thereby playing a critical role in the safe operation of coal mines. As coal mining operations extend to greater depths, they introduce heightened challenges for safe transportation, compounded by increased equipment loss. Consequently, there is a pressing need to enhance safety protocols to safeguard personnel and materials. Traditional maintenance and repair methods, characterized by routine equipment inspections and scheduled downtime, often fall short in addressing emerging issues promptly, leading to production delays and heightened risks for maintenance personnel. This underscores the necessity of adopting predictive maintenance strategies, leveraging digital twin models to anticipate and prevent potential faults in mine hoists. In summary, the implementation of predictive maintenance techniques grounded in digital twin technology represents a proactive and scientifically rigorous approach to ensuring the continued safe operation of mine hoists amidst the evolving challenges of deepening coal mining operations. In this study, we propose the integration of a CNN-LSTM algorithm within a digital twin framework for predicting faults in mine hoist braking systems. Utilizing software such as AMESim 2019 and MATLAB 2016b, we conduct joint simulations of the hoist braking digital twin system. Subsequently, leveraging the simulation model, we establish a fault diagnosis platform for the hoist braking system. Finally, employing the CNN-LSTM network model, we forecast failures in the mine hoist braking system. Experimental findings demonstrate the effectiveness of our proposed algorithm, achieving a prediction accuracy of 95.35%. Comparative analysis against alternative algorithms confirms the superior performance of our approach. [ABSTRACT FROM AUTHOR]

The Himalayan marmot (Marmota himalayana), a natural host and transmitter of plague, is also susceptible to the hepadnavirus infection. To reveal the genetic basis of the hepadnavirus susceptibility and the immune response to plague, we systematically characterized the features of immune genes in Himalayan marmot with those of human and mouse. We found that the entire major histocompatibility complex region and the hepatitis B virus pathway genes of the Himalayan marmot were conserved with those of humans. A Trim (tripartite motif) gene cluster involved in immune response and antiviral activity displays dynamic evolution, which is reflected by the duplication of Trim5 and the absence of Trim22 and Trim34. Three key regions of Ntcp, which is critical for hepatitis B virus entry, had high identity among seven species of Marmota. Moreover, we observed a severe alveolar hemorrhage, inflammatory infiltrate in the infected lungs and livers from Himalayan marmots after infection of EV76, a live attenuated Yersinia pestis strain. Lots of immune genes were remarkably up-regulated, which several hub genes H2r[gamma], Tra29, and Nlrp7 are placed at the center of the gene network. These findings suggest that Himalayan marmot is a potential animal model for study on the hepadnavirus and plague infection. Key words: Himalayan marmot, immune system, hepadnavirus, plague. La marmotte de l'Himalaya (Marmota himalayana), un hote naturel qui peut transmettre la peste, est egalement sensible a l'infection par l'hepadnavirus. Afin de reveler l'assise genetique de la sensibilite a l'hepadnavirus et de la reponse immunitaire a la peste, les auteurs ont systematiquement caracterise les genes du systeme immunitaire chez la marmotte de l'Himalaya avec ceux chez l'humain et la souris. Les auteurs ont trouve que la region entiere du complexe majeur d'histocompatibilite et les genes du sentier du virus de l'hepatite B chez la marmotte de l'Himalaya sont conserves avec ceux presents chez l'humain. Un groupe de genes Trim (<< a motif tripartite >>) implique dans la reponse immunitaire et l'activite antivirale presentait une evolution dynamique, laquelle se reflete par la duplication de Trim5 et l'absence des genes Trim22 et Trim34. Trois regions cles de Ntcp, lequel est critique pour l'entree du virus de l'hepatite B, presentaient un fort niveau d'identite au sein de sept especes de Marmota. De plus, les auteurs ont observe une severe hemorragie alveolaire, un infiltrat inflammatoire dans les poumons et le foie chez des marmottes de l'Himalaya apres infection avec l'EV76, une souche vivante attenuee du Yersinia pestis. Plusieurs genes du systeme immunitaire etaient remarquablement plus fortement exprimes, dont plusieurs genes (H2r[gamma], Tra29 et Nlrp7) qui sont au coeur de reseaux de genes. Ces observations suggerent que la marmotte de l'Himalaya constitue une espece modele potentielle pour l'etude de l'infection avec l'hepadnavirus et la peste. [Traduit par la Redaction] Mots-cles : marmotte de l'Himalaya, systeme immunitaire, hepadnavirus, peste., Introduction The Himalayan marmot (Marmota himalayana) is a marmot species that inhabits alpine grasslands throughout the Himalayan regions and on the Tibetan Plateau (Nikol'skii and Ulka 2006; Hoffmann et al. [...]

Wide heterogeneity exists in cancer patients' survival, ranging from a few months to several decades. To accurately predict clinical outcomes, it is vital to build an accurate predictive model that relates the patients' molecular profiles with the patients' survival. With complex relationships between survival and high‐dimensional molecular predictors, it is challenging to conduct nonparametric modeling and irrelevant predictors removing simultaneously. In this article, we build a kernel Cox proportional hazards semi‐parametric model and propose a novel regularized garrotized kernel machine (RegGKM) method to fit the model. We use the kernel machine method to describe the complex relationship between survival and predictors, while automatically removing irrelevant parametric and nonparametric predictors through a LASSO penalty. An efficient high‐dimensional algorithm is developed for the proposed method. Comparison with other competing methods in simulation shows that the proposed method always has better predictive accuracy. We apply this method to analyze a multiple myeloma dataset and predict the patients' death burden based on their gene expressions. Our results can help classify patients into groups with different death risks, facilitating treatment for better clinical outcomes. [ABSTRACT FROM AUTHOR]

As the manufacturing industry evolves, the significance of control valve positioners in chemical production escalates. The flapper–nozzle system, the heart of control valve positioners, directly influences the linearity of system control. Presently, studies on the flapper–nozzle system primarily focus on dynamic system modeling and computational fluid dynamics simulations. However, traditional flapper–nozzle mechanisms often fail to achieve linear control objectives. This paper proposes a novel negative-pressure nozzle structure to tackle this issue, combining computational fluid dynamics and experimental methods, and considering gas compressibility during high-speed flow. Both simulation and experimental results suggest that the new structure improves the supply air pressure and broadens the linear pressure output range of the system, showing significant potential for practical applications. [ABSTRACT FROM AUTHOR]

Concentration of emulsion has a significant influence on the working performance and service life of hydraulic supports.In this paper, existing approaches of emulsion concentration detection were analyzed. Based on liquid refration index CCD Method of measurement for the refractive index of fluid, an automatic measurement device for the refractive index of emulsion was developed, and then the relationship between concentration and refractive index of emulsion has been investigated by experimental study through the developed device.According to the theory of light scattering suspension, a method for determining the concentration of emulsion by measuring the refractive index of emulsion was proposed.Finally, the on-line detecting method based on optical refractive principle has been studied.

This paper proposes a temporary support system for improving the efficiency and safety of underground roadway excavation in coal mines. Firstly, this study establishes a calculation model for the initial supporting force of the excavation of roadway temporary support and a gray system-based automatic prediction model for the initial supporting force level, based on the mechanism of temporary support controlling the roof. These models enable the prediction of the required initial supporting force at different locations along the roadway's temporary support area, thereby providing a basis for controlling the initial supporting force of the temporary support system. To achieve efficient and adaptive control of the initial supporting force of temporary supports at different locations, this study designs a support force controller based on Simulated Annealing Particle Swarm Optimization Proportional-Integral-Derivative (SAPSO-PID). This study establishes a mathematical model for the hydraulic cylinder pressure system controlled by the temporary support overflow valve and conducts a stability analysis and model verification. The study constructs a simulation control system for the initial supporting force based on SAPSO-PID using the combined simulation platform of AMESim and Matlab. The simulation results demonstrate that the proposed support force control system efficiently achieves adaptive control of the initial supporting force of temporary supports. An experimental system in the underground roadway of a coal mine is constructed to validate the results of the simulation analysis. [ABSTRACT FROM AUTHOR]

The subway alleviates the traffic pressure in the city but also brings the potential risk of land subsidence. The land subsidence caused by the subway is a global problem that seriously affects the safety of subway operations and surrounding buildings. Therefore, it is very important to carry out long-term deformation monitoring on the subway system. StaMPS-PS is a time-series Interferometric Synthetic Aperture Radar (InSAR) technique that serves as an effective means for monitoring urban ground subsidence. However, the accuracy of external (Digital Elevation Models) DEM will affect the accuracy of StaMPS-PS monitoring, and previous studies have mostly used SRTM-1 arc DEM (30 m) as the external DEM. In this study, to obtain a more precise measurement of surface deformation caused by the excavation of the Hohhot subway, a total of 85 scenes of Sentinel-1A data from July 2015 to October 2021, as well as two different resolution digital elevation models (DEMs) (ALOS PALSAR DEM and SRTM-1 arc DEM), were used to calculate and analyze the subsidence along the subway line in Hohhot city. The StaMPS-PS monitoring results showed the ALOS PALSAR DEM, as an external DEM, had higher accuracy, and there was regional subsidence in both the construction processes of Line 1 and Line 2 of the Hohhot subway, with a maximum subsidence rate of −21.1 mm/year. The dynamic changes in subway subsidence were fitted using the Peck formula and the long short-term memory (LSTM) model. The Peck formula results showed the width and maximum subsidence of the settlement troughs gradually expanded during the construction of the subway. The predicted values of the Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) of the LSTM model were less than 4 mm and 10%, respectively, consistent with the measured results. Furthermore, we discussed the factors that affect settlement along the subway line and the impact of two external DEMs on StaMPS-PS. The study results provide a scientific method for DEM selection and subsidence analysis calculations in the StaMPS-PS monitoring of urban subway subsidence. [ABSTRACT FROM AUTHOR]