Background: Malnutrition is common in patients with acute myocardial infarction (AMI) and is associated with a poor prognosis. The prognostic value of the prognostic nutritional index (PNI) in patients with AMI remains controversial. We aimed to explore the relationship between PNI and all-cause mortality in critically ill patients with AMI and evaluate the incremental prognostic value of PNI to commonly used prognostic assessment tools. Methods: The Medical Information Mart for Intensive Care-IV (MIMIC-IV) database was used to conduct a retrospective cohort analysis on 1180 critically ill patients with AMI. The primary endpoints were defined as 6-month and 1-year all-cause mortality. Cox regression analysis was used to investigate the relationship between admission PNI and all-cause mortality. The effect of adding PNI to sequential organ failure assessment (SOFA) score, or charlson comorbidity index (CCI) on its discriminative ability was assessed using C-statistic, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Results: Multivariate cox regression analysis demonstrated that the low PNI was regarded as an independent predictor of 1-year all-cause mortality in AMI patients admitted to ICU (adjusted Hazard Ratio: 95% CI = 1.75 (1.22–2.49)). The ROC test showed that admission PNI had a moderate predictive ability to predict all-cause mortality of critically ill patients with AMI. Furthermore, the net reclassification and integrated discrimination of the CCI alone model improved significantly with PNI. [C-statistic increased from 0.669 to 0.752, p < 0.001; NRI = 0.698, p < 0.001; IDI = 0.073, p < 0.001]. When PNI was added to the SOFA score, the C-statistic significantly improved from 0.770 to 0.805 (p < 0.001), and the NRI and IDI were estimated at 0.573 (p < 0.001) and 0.041 (p < 0.001), respectively. Conclusion: PNI could be a novel predictor for identifying patients at high risk of 1-year all-cause mortality in critically ill patients with AMI. The addition of PNI to the SOFA score or CCI may be useful for very early risk stratification.

Li P, et al. J Gynecol Oncol. 2020 Oct;32:e17. https://doi.org/10.3802/jgo.2021.32.e17

Because of their superior performance, flexible strain sensors are used in a wide range of applications, including medicine and health, human–computer interaction, and precision manufacturing. Flexible strain sensors outperform conventional silicon-based sensors in high-strain environments. However, most current studies report complex flexible sensor preparation processes, and research focuses on enhancing and improving one parameter or property of the sensors, ignoring the feasibility of flexible strain sensors for applications in various fields. Since the mechanical properties of flexible sensors can be well combined with rubber conveyor belts, in this work polydimethylsiloxane (PDMS) was used as a flexible substrate by a simple way of multiple drop coating. Graphene-based flexible strain sensor films that can be used for strain detection at the joints of steel cord core conveyor belts were successfully fabricated. The results of the tests show that the sensor has a high sensitivity and can achieve a fast response (response time: 43 ms). Furthermore, the sensor can still capture the conveyor belt strain after withstanding high pressure (1.2–1.4 MPa) and high temperature (150 °C) during the belt vulcanization process. This validates the feasibility of using flexible strain sensors in steel wire core conveyor belts and has some potential for detecting abnormal strains in steel wire core conveyor belt, broadening the application field of flexible sensors.

The pore and fracture structure of coal is the main factor that affects the storage and seepage capacity of coalbed methane. The damage of coal structure can improve the gas permeability of coalbed methane. A coal sample with a drilled hole was kept inside of a custom-designed device to supply confining pressure to the coal sample. Liquid nitrogen was injected into the drilled hole of the coal sample to apply cyclic cold loading. Confining pressures varying from 0~7 MPa to the coal sample were applied to explore the relationship between the structural damage and confining pressure. The structural damage rules of coal samples under different confining pressure were revealed. The results showed that: (1) The structural damage degree of the coal sample increases with the increase of confining pressure; (2) The coal sample was broken after three cycles of cold loading under 7 MPa confining pressure; (3) Without confining pressure, the coal sample is more likely to be damaged or even destroyed by cold liquid nitrogen. (4) The fracture extends along the stratification direction of coal samples, which is significant for coal samples with original fractures, but not obvious for the coal sample without fracture. The research results provide a new method and theoretical basis for permeability improvement of the coal seam.

In this paper, the ant colony optimization (ACO) algorithm is introduced into the ship weather routing problem, aiming at finding the optimal route for transoceanic ships quickly, efficiently and accurately. The author has improved the traditional ACO algorithm in two aspects. Firstly, the ant moving rule is modified so that ants are more purposeful when searching for route points. Then, pheromone updating rule is improved to increase algorithm convergence speed and avoid local optima. Finally, the improved ACO algorithm is applied to the route optimization simulation experiment under the weather conditions. It has been verified that the improved ACO algorithm has better performance in route smoothness and convergence speed. The simulation results of MATLAB show that the algorithm can not only find a shorter distance route from starting point to end, but also ensure that the navigation time of the route is relatively short. Besides, the optimized route planned by the algorithm can also avoid the dangerous areas encountered in the course of navigation in time and ensure the safety of the ship at sea.

In order to improve the tribological properties of titanium substrate, self-assembly technique was used to prepare a graphene-silane coating: RGO-APTES coating on titanium substrate. The γ-aminopropyltriethoxysilane (APTES) was used to prepare a self-assembled APTES coating as a function of adhesive interlayer, aiming to improve the assembly efficient for graphene coating. The influence of that interlayer on the assembly and tribological properties of graphene coatings on titanium substrate was investigated. Morphology, thickness, chemical characteristic and tribological tests were utilized to investigate the assembly process and tribological properties of coatings. The results show that: 1) the pH values of APTES aqueous solution plays an important role in the molecule orientation of the APTES interlayer, and thus the properties of graphene coating is influenced. When pH is approximately 8.5, the molecule orientation of the interlayer is consistent, so that it has improved adsorption effect on graphene sheets and the graphene coating is uniformly distributed and well-covered; 2) the thickness influences the tribological properties of graphene-APTES coating -- single layered APTES interlayer provides a stronger interlayer strength. The obtained RGO-APTES2 samples have novel friction reducing and wear resisting properties, and can be applied on the surface of titanium substrate as lubricating coating.