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Nowadays, poverty-stricken college students have become a special group among college students and occupied a higher proportion in it. How to accurately identify poverty levels of college students and provide funding is a new problem for universities. In this study, a novel model, which incorporated Random Forest with Principle Components Analysis (RF-PCA), is proposed to predict poverty levels of college students. To establish this model, we collect some useful information is to construct the datasets which include 4 classes of poverty levels and 21 features of poverty-stricken college students. Furthermore, the feature dimension reduction consists of two steps: the first step is to select the top 16 features with the ranking of feature, according to the Gini importance and Shapley Additive explanations (SHAP) values of features based on Random Forest (RF) model; the second step is to extract 11 dimensions by means of Principle Components Analysis (PCA). Subsequently, confusion metrics and receiver operating characteristic (ROC) curves are utilized to evaluate the promising performance of the proposed model. Especially the accuracy of the model achieves 78.61%. Finally, compared with seven states of the art classification algorithms, the proposed model achieves a higher prediction accuracy, which indicates that the results provide great potential to identify the poverty levels of college students.

Intramuscular fat (IMF) is an essential trait closely related to meat quality. The IMF trait is a complex quantitative trait that is regulated by multiple genes. In order to better understand the process of IMF and explore the key factors affecting IMF deposition, we identified differentially expressed mRNA, miRNA, and lncRNA in the longissimus dorsi muscle (LD) between Songliao Black (SL) pigs and Landrace pigs. We obtained 606 differentially expressed genes (DEGs), 55 differentially expressed miRNAs (DEMs), and 30 differentially expressed lncRNAs (DELs) between the SL pig and Landrace pig. Enrichment results from GO and KEGG indicate that DEGs are involved in fatty acid metabolism and some pathways related to glycogen synthesis. We constructed an lncRNA–miRNA–mRNA interaction network with 18 DELs, 11 DEMs, and 42 DEGs. Finally, the research suggests that ARID5B, CPT1B, ACSL1, LPIN1, HSP90AA1, IRS1, IRS2, PIK3CA, PIK3CB, and PLIN2 may be the key genes affecting IMF deposition. The LncRNAs MSTRG.19948.1, MSTRG.13120.1, MSTRG.20210.1, and MSTRG.10023.1, and the miRNAs ssc-miRNA-429 and ssc-miRNA-7-1, may play a regulatory role in IMF deposition through their respective target genes. Our research provides a reference for further understanding the regulatory mechanism of IMF.

Heterogeneous GPU clusters play an important role in processing parallel applications and massive data sets in the cloud platform. However, due to the diversity of GPU types, how to effectively allocate various GPU types is a challenge. This paper first analyzes the characteristics of request and allocation for various GPU types based on Alibaba cluster data. Then we propose a method to adaptively select the best model to predict demand of various GPU types, and feature extraction from the best model. Further, we design a model based on Long Short Term Memory (LSTM) to forecast allocation of each GPU type. Finally, the extensive experimental results demonstrate the promising performance compared with multiple baseline methods by using real-world trace data from Alibaba cloud data centers. The trial illustrates that the demand prediction accuracy of the adaptive selection method reaches 87%, while the proposed prediction allocation model yields better performances with root mean square error and mean absolute error of 1.78 and 0.85, respectively.

Background Accumulating evidence suggests that pregnancy-related anxiety (PRA) has adverse impacts on maternity health and infant development. A substantial body of literature has documented the important influence of family function, perceived social support and resilience on PRA. However, research identifying the mediating mechanisms underlying this relationship in China are still lacking. Therefore, the current study aimed to investigate the prevalence of PRA under the three-child policy in China, and also explore whether resilience mediated the effect of family function and perceived social support on PRA. Methods A total of 579 pregnant women were recruited in this cross-section study from a teaching hospital in Chongqing, China. Participants were required to complete the following questionnaires: the demographic form, the Chinese Pregnancy-related Anxiety scale, the 10-item Connor-Davidson Resilience Scale, the APGAR Family Care Index Scale, and Multidimensional Scale of Perceived Social Support. Pearson correlation analysis was utilized to examine the rudimentary relationship among the study variables. Bootstrapping analyses in the structural equation modeling were applied to identify the significance of indirect effects. Results There were 41.4% of pregnant Chinese women indicating PRA. Correlational analyses indicated that perceived social support, family function and resilience were negatively associated with PRA (r = -0.47, P r = -0.43, P r = -0.37, P CI [-0.184, -0.021]) and family function (β = -0.049, 95% CI [-0.103, -0.011]) on PRA via resilience. Conclusions Chinese pregnant women are suffering from high levels of PRA. Better family function and perceived social support might reduce the occurrence of PRA, as well as by the mediating effects of resilience.

In recent years, many researchers have studied on the hydrogen storage properties of metal-organic frameworks (MOFs) by grand canonical Monte Carlo (GCMC) simulation. At present, the GCMC studies of Cu-BTC (BTC: benzene-1,3,5-tricarboxylate) which is a prototypical metal-organic framework mainly adopt the classical force fields, the simulation temperatures are mainly focus on 298 and 77 K, and most researchers did not consider the effects of quantum effects at low temperature. Therefore, we used the quantum effects to correct the classical force fields and the force fields with more accurate simulation results were used to simulate the hydrogen adsorption performances of Cu-BTC in the temperature range of 77–298 K and the pressure range of 1–8 MPa at each temperature. The results show that the effects of quantum effects on the hydrogen storage of Cu-BTC cannot be neglected and the corrected Dreiding force field can simulate hydrogen adsorption performances of Cu-BTC more accurately at low temperature. © 2017 American Institute of Chemical Engineers AIChE J, 2017

Two-phase pressure drop of LNG (liquefied natural gas) during flow boiling has been measured in a horizontal smooth tube with an inner diameter of 8 mm at 0.3–0.7 MPa. And the experiments was conducted with the mass flux of 50–200 kg m−2 s−1, heat flux of 8–32 kW m−2, and vapor quality of 0.16–0.83. The effects of vapor quality, heat flux and mass flux, inlet pressure on the frictional pressure drop of LNG are discussed. The comparisons of the experimental data with the predicted value by existing six correlations are analyzed. Muller-Steinhagen and Heck [8] and Friedel [21] can provide acceptable predictions for two-phase pressure drop of LNG at inlet pressure of 0.3–0.7 MPa among them.

This paper presents an experimental investigation on the heat transfer characteristics of liquefied natural gas flow boiling in a vertical micro-fin tube. The effect of heat flux, mass flux and inlet pressure on the flow boiling heat transfer coefficients was analyzed. The Kim, Koyama, and two kinds of Wellsandt correlations with different Ftp coefficients were used to predict the flow boiling heat transfer coefficients. The predicted results showed that the Koyama correlation was the most accurate over the range of experimental conditions.

Two-phase heat transfer and pressure drop of LNG (liquefied natural gas) have been measured in a horizontal smooth tube with an inner diameter of 8 mm. The experiments were conducted at inlet pressures from 0.3 to 0.7 MPa with a heat flux of 8–36 kW m−2, and mass flux of 49.2–201.8 kg m−2 s−1. The effect of vapor quality, inlet pressure, heat flux and mass flux on the heat transfer characteristic are discussed. The comparisons of the experimental data with the predicted value by existing correlations are analyzed. Zou et al. (2010) correlation shows the best accuracy with 24.1% RMS deviation among them. Moreover four frictional pressure drop methods are also chosen to compare with the experimental database.

In this study, dense composite electrolytes with different H3PO4 doping levels were fabricated. The conductivity property is optimized giving consideration to the influence of H3PO4 doping level. The result of SEM image indicates that the composite of 1P1S-7 is sufficiently dense. The conductivities increase with the order: σ (1P1S)

The presence of polyethylene glycol (PEG) in a co-impregnation process reduced the crystallite size of Co3O4 and formed a close contact between the uniformly distributed RuO2 and Co3O4 particles on CoRuOx/SiO2 sample after calcination. This structure facilitated the reduction of small Co3O4 particles. The resultant small Co0 particles and Co-Ru synergistic effect enhanced the Co-time yield and turnover frequency (TOF) in Fischer–Tropsch synthesis. Comparatively, the PEG-free process led to the inhomogeneous distribution and segregation of RuO2 particles. These separated RuO2 precursors could improve the reduction of Co3O4, but had less impact on TOF in contrast to Ru-free Co/SiO2 catalyst.

Uncertainty of building energy demands has large influence on accuracy of building cooling heating and power (BCHP) programming model. Uncertain programming model is proposed to optimize BCHP system with consideration of uncertainty of energy demands. Monte-Carlo method (MCM) and mixed-integer nonlinear programming (MINLP) are integrated in the model (M–M model for short). MCM can be used to simulate the uncertainty of energy demands avoiding dimension disaster and complex calculation. Correlation between different energy demands can also be considered in the model. And facility scheme and operation strategy can be optimized simultaneously in MINLP model. A numerical example is calculated with the M–M model. Convergence rate of expected values of the variables optimized in the model is high. Influence of energy demand uncertainty is studied with investigation of expected values, standard deviations of evaluation indicators and facility capacities. Sensitivity of the parameters to energy demand uncertainty is much different. It is unnecessary to consider uncertainty of energy demands when evaluating system feasibility with indicators of annual cost saving rate and annual natural gas saving rate, for they are influenced only a little by uncertainty of energy demands. While uncertainty of energy demands must be considered when studying parameters related to assistant facilities, which are very sensitive to the uncertainty. The result is valuable for designing strategy of facility scheme.

Effect of working temperature on the resistance characteristic including the permeability coefficient and the pressure drop evolution of a pleated stainless steel woven filter with a nominal pore size of 0.5 μm has been studied. The permeability coefficient was obtained based on the pressure drop data and the Darcy's law. In three filtration experiments, pure carbon dioxide at 283 K, nitrogen at 85 K and liquid helium at 18 K are adopted, respectively. It is found that the permeability coefficient decreases at the working temperature due to the cold shrink of the filter element at cryogenic temperature. Then, two kinds of feed slurries, mixture of liquid nitrogen and solid carbon dioxide at 85 K, and mixture of liquid helium and solid nitrogen at 18 K, flow into the filter cell. The solid particles are deposited on the filter surface to form a filter cake and the purified liquid flows through the filter. It is found that the pressure drop evolution shows the same trend on these two temperatures, which can be divided into three stages with high filtration efficiency, indicating the feasibility of the filter for cryogenic application. However, variant cake resistances are obtained, which is resulted from the different interactions between solid particles in the feed slurry at lower working temperature.

This paper presents an investigation of a new method of purifying cryogenic liquid using sintered metallic wire-mesh filter, which has the advantages of high purifying efficiency and preferred strength at absolutely low temperature. Experiments are conducted to purify solid CO2 particles from liquid nitrogen. Temperature and pressure in the upstream and downstream of the filter, and the flow rate of carbon dioxide (CO2) gas and liquid nitrogen are measured, with the gas content of filtrate analyzed using a CO2 concentration detector. It is illustrated that after filtration, the purity of liquid nitrogen (volume fraction) is higher than 99.99%, which means that the volume fraction of CO2 is less than 0.01%. Effects of operation parameters on the performance of the filter, such as pressure drop Δp and filtration efficiency E are analyzed quantitatively. The present conclusions will provide a guideline to the optimumal design and operation of sintered metallic wire-mesh filter in cryogenic application.

Closure correlations describing bubble nucleation and departure on the heating surface is indispensable when modeling subcooled boiling flow using a two-fluid model. Due to the small contact angle and surface tension, nucleation and departure of nitrogen vapor bubble has different characteristics to those of high-boiling liquids. For the purpose of accurate two-fluid model formulation, these factors have to be taken into consideration. In this study, some closure correlations of the bubble departure diameter, active site density and bubble waiting time were tested in the frame of the two-fluid model and the CFX code. Benchmark experiments were then performed to evaluate the correlations. Comparison of the numerical results against the experimental data demonstrates that the surface tension is crucial to modeling the bubble departure diameter and the active site density. The bubble waiting time correlation formulated according to bubble growth is expected to be used as a criterion of judging the transition from subcooled to saturated boiling.

Sensitivity analysis of energy demands is carried out in this paper to study their influence on performance of CCHP system. Energy demand is a very important and complex factor in the optimization model of CCHP system. Average, uncertainty and historical peaks are adopted to describe energy demands. The mix-integer nonlinear programming model (MINLP) which can reflect the three aspects of energy demands is established. Numerical studies are carried out based on energy demands of a hotel and a hospital. The influence of average, uncertainty and peaks of energy demands on optimal facility scheme and economic advantages of CCHP system are investigated. The optimization results show that the optimal GT’s capacity and economy of CCHP system mainly lie on the average energy demands. Sum of capacities of GB and HE is equal to historical heating demand peaks, and sum of capacities of AR and ER are equal to historical cooling demand peaks. Maximum of PG is sensitive with historical peaks of energy demands and not influenced by uncertainty of energy demands, while the corresponding influence on DH is adverse.

The assembled form of thick-wall glass fiber reinforced plastics (GFRP) tube and 0Cr18Ni9 austenitic stainless steel pipes was designed as the radius thermal-insulating and load-supporting structure in cryogenic vessels. In order to study the thermal leakage and gap changes on the support structure, as well as radius temperature and stress distribution on GFRP tube, an experimental investigation has been taken. The results indicate that the support structure is proved to fit well as thermal-insulating and load-supporting part in cryogenic vessels, furthermore has high security during cryogenic applications.

The characteristics of overall pressure drop during upward boiling two-phase flow of nitrogen with constant mass flux and varying heat flux are experimentally investigated using a vertical tube with an inner diameter of 6.0 mm and numerically simulated using the two-fluid model with new closure correlations. Comparison of the numerical results against the experimental data shows that prior to the transition point in the curve of pressure drop evolution, the predicted pressure drop is in a satisfactory agreement with the experimental data. The present study demonstrates that both the wall lubrication force modeling and the bubble diameter modeling have significant effect on the pressure drop prediction. Both the theoretical analysis and the experimental evidence suggest that the transition point in the pressure drop evolution curve reflects the bubbly-to-slug flow regime transition.

The wave equation describes how seismic waves propagate in the subsurface. Inversion methods based on the wave equation naturally take into account the complex behavior of propagating waves and can be used to make accurate estimates of model parameters. However, computational cost and poor convergence have not been overcome, and thus restrict the broad application of this technique. Preconditioned conjugate gradient inversion using back-propagation techniques is a simple, robust implementation of wave-equation inversion in which the step length for correcting the model for each iteration is a crucial factor affecting convergence and hence computational cost. The step length can be calculated by an adaptive controller based on the theory of model reference nonlinear control that ensures that the error energy of the complex system vanishes rapidly. Although the computational cost for each iteration remains the same, the inversion is robust and converges more rapidly than other methods. We tested our method on synthetic data generated from a three-layer fractured model. The inversion converges to the true model after five iterations, and different initial models give similar inversion results. The application to 2D real data from a gas field in western China illustrates that even two iterations yield unambiguous interpretable inversion sections.

The classic differential effective medium (DEM) theory can be used to determine the elastic properties of the porous medium, but the final elastic properties of multiple-porosity rock depend on the added order of the different pore-type inclusions. This paper presents a differential effective medium model for multiple-porosity rock and derives the analytical solutions of the bulk and shear moduli for dry rock. The validity of these analytical approximations is tested by integrating the full DEM equation numerically. The analytical formulae give good estimates of the numerical results over the whole porosity range. The analytical formulae have been used to predict the elastic moduli for the sandstone experimental data by assuming that the porous rock contains dual-porosity of both cracks and pores. The results show that they can accurately predict the variations of elastic moduli with porosity for dry sandstones.

The two-fluid model has been extensively used in modeling boiling flow of water, however, there are few equivalent studies of boiling flow of cryogenic liquids. In the present study, the two-fluid model which is basically included in the CFX code was modified by incorporating new closure correlations, then boiling flow of liquid nitrogen in a vertical tube was numerically simulated using the basic model and the modified model, respectively. Comparison with experimental data shows that the modified model is satisfactorily improved in accuracy. This study demonstrated that the following parameters and models are important for accurate prediction: the lift force, the bubble diameter distribution and the active site density, among which, the active site density has the most significant effect.

Litho-stratigraphic reservoir is very important in the oil and gas industry. The image of the reservoir is critical to the layout of well and drilling in the oil and gas exploration and production. The purpose of our study is to construct a new imaging function and a new imaging condition to produce the image of the reservoir based on the results of acoustic full waveform inversion and rock physics. The imaging function is then combined with porosity and fluid bulk modulus which are obtained from the inversion results and are closely related to the physical characteristics of reservoir. The feasibility and effectiveness of the method is best illustrated by successful application to a synthetic test and a field data example.

Publisher Summary This chapter analyzes the optimization of three kinds of Peakshaving LNG cycles —namely, nitrogen–methane expansion liquefaction cycle, propane pre-cooled mixed refrigerant liquefaction cycle, and two stages mixed refrigerant liquefaction cycle. The specific power consumption of unit LNG production is used as the objective function. The results of optimization analysis indicate the power consumption of C3H8 pre-cooling mixed refrigerant liquefaction cycle is the least and power consumption of N2-CH4 expander liquefaction cycle is the largest. N2-CH4 expansion liquefaction cycle is compact, flexible and with good applicability but its power consumption is large, so it's suitable for small and medium-sized LNG system, which is used to recycle natural gas resources of marginal gas field. C3H8 pre-cooling mixed refrigerant liquefaction cycle has complicated equipments, its power consumption is low, so it is suitable for large-sized base load LNG system. The three kind cycles are optimized with specific power consumption of unit LNG product as objective function. The optimum results are the optimum value of the objective function and the corresponding process parameters.