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In the treatment of transverse olecranon fractures, complicated tension band wiring (TBW) has high rates of re-operations. Besides, plate fixation (PF) and TBW both have large surgical incisions and soft-tissue irritation. Therefore, the new cross-locking intramedullary nail (CIN) with easy handling and minimally invasive features is significantly advantageous. The goal of this study was to biomechanically compare CIN with TBW for fixing transverse olecranon fracture.The transverse olecranon fracture models were created with 15 fresh-frozen cadaveric ulnae which were randomly divided into 3 groups: one group for TBW fixation, another for CIN fixation with 1 conical locking screw (CIN-1), and the last for CIN fixation with 3 conical locking screws (CIN-3). The stiffness, cyclic stability, and failure strength of the fixed fracture models were compared after the corresponding experimental tests.The failure strength of TBW, CIN-1 and CIN-3 were (313.38±27.68) N, (528.56±53.58) N and (871.04±94.95) N. There was a significant difference between them. However, as for dynamic stability and stiffness, CIN-3 was higher and TBW was lower, with no significant differences between the groups.The biomechanical properties of CIN were superior to those of TBW, and CIN was more stable and solid for fixing transverse olecranon fracture, of which CIN-3 was the strongest.

Intrathoracic anastomosis and cervical anastomosis are very common in the esophagectomy of esophageal cancer; we aimed to evaluate the effects and safety of intrathoracic anastomosis versus cervical anastomosis in the esophagectomy.We searched PubMed, EMBASE, Cochrane Library, Web of Knowledge, China National Knowledge Infrastructure, and WanFang databases up to September 30, 2021, for randomized controlled trials focused on cervical anastomosis versus intrathoracic anastomosis for the treatment of esophageal cancer.In total, 12 randomized controlled trials involving 1,493 patients were finally included. The incidence of anastomotic leak [relative risk = 2.76, 95% confidence interval (1.94∼3.94), P.001] and recurrent laryngeal nerve injury [relative risk = 6.12, 95% confidence interval (3.02∼12.41), P.001] in the intrathoracic anastomosis group were less than that of the cervical anastomosis group. There were no significant differences in the incidence of anastomotic stenosis [relative risk = 1.33, 95% confidence interval (0.88∼2.00), P = .18], pneumonia [relative risk = 1.31, 95% confidence interval (0.82∼2.09), P = .25], postoperative chylothorax [relative risk = 1.01, 95% confidence interval (0.40∼2.52), P = .99], and mortality [relative risk = 0.93, 95% confidence interval (0.52∼1.68), P = .82] between the 2 groups.Intrathoracic anastomosis is associated with significantly reduced risk of leak and recurrent laryngeal nerve injury compared with cervical anastomosis.

Time to event outcomes is commonly encountered in epidemiologic research. Multiple papers have discussed the inadequacy of using the hazard ratio as a causal effect measure due to its noncollapsibility and the time-varying nature. In this paper, we further clarified that the hazard ratio might be used as a conditional causal effect measure, but it is generally not a valid marginal effect measure, even under randomized design. We proposed to use the restricted mean survival time (RMST) difference as a causal effect measure, since it essentially measures the mean difference over a specified time horizon and has a simple interpretation as the area under survival curves. For observational studies, propensity score adjustment can be implemented with RMST estimation to remove observed confounding bias. We proposed a propensity score stratified RMST estimation strategy, which performs well in our simulation evaluation and is relatively easy to implement for epidemiologists in practice. Our stratified RMST estimation includes two different versions of implementation, depending on whether researchers want to involve regression modeling adjustment, which provides a powerful tool to examine the marginal causal effect with observational survival data.

Acoustic signals have attracted considerable attention in mechanical fault diagnosis because of their advantages in non-invasive technique, instant measurement and low cost. However, traditional fault diagnosis methods could not achieve accurate feature extraction because of the strong noise environment of acoustic signals. In view of this, this study aims to provide a method that could accurately extract effectiveness features under noisy environment. Sparse representation is a research hotspot in intelligent fault diagnosis and has shown great power in feature extraction. In this paper, a novel fault diagnosis method based on parallel sparse filtering is presented to achieve sparse feature extraction from acoustic signals. Specially, parallel sparse filtering achieves sparse feature exaction by adding another normalization direction based on sparse filtering, and the derivation of parallel sparse filtering is also presented in detail. Then Z-score normalization is used to activate the training and testing data in fault classification process. The superiority of the proposed method is validated by simulated and experimental data. The results show that PSF is a promising sparse feature extraction method that can be used for mechanical fault diagnosis under acoustic signals.

When estimating the average causal effect in observational studies, researchers have to tackle both self-selection of treatment and outcome modeling. This is difficult because the parametric form of the outcome model is often unknown and there exists a large number of covariates. In this work, we present a semiparametric strategy for estimating the average causal effect by regressing on the propensity score. Furthermore, we show that regression error terms usually depend on the propensity score as well, which could cause heteroscedastic variances, and thus construct a refined estimator to improve the estimation efficiency. Both estimators are shown to be consistent and asymptotically normally distributed, with the latter one having a smaller asymptotic variance. The simulation studies indicate that our methods compare favorably with many competing estimators. Our methods are easy to implement and avoid hazardous impact due to extreme weights as often seen in weighting estimators. They can also be extended to handle subgroup effects with known structure. We apply the proposed methods to data from the Ohio Medicaid Assessment Survey 2012, estimating the effect of having health insurance on self-reported health status for a population with subsidized insurance plan choices under the Affordable Care Act.

The enrichment of low concentration coalbed methane using adsorption process with activated carbon adsorbent was studied in this work. Adsorption isotherms of methane, nitrogen and carbon dioxide on activated carbon were measured by volumetric method, meanwhile a series of breakthrough tests with single component, binary components and three components feed mixture has been performed for exploring dynamic adsorption behaviors. Moreover, a rigorous mathematical model of adsorption bed containing mass, energy, and momentum conservation equation as well as dual-site Langmuir model with the Linear driving force model for gas–solid phase mass transfer has been proposed for numerical modeling and simulation of fixed bed breakthrough process and vacuum pressure swing adsorption process. Furthermore, the lumped mass transfer coefficient of methane, nitrogen and carbon dioxide on activated carbon adsorbent has been determined to be 0.3 s−1, 1.0 s−1 and 0.06 s−1 by fitting the breakthrough curves using numerical calculation. Additionally, a six bed VPSA process with twelve step cycle sequence has been proposed and investigated for low concentration coalbed methane enrichment. Results demonstrated that the methane molar fraction in feed mixture ranged from 10% to 50% could be enriched to 32.15% to 88.75% methane in heavy product gas with a methane recovery higher than 83% under the adsorption pressure of 3 bar (1 bar = 105 Pa) and desorption pressure of 0.1 bar. Energy consumption of this VPSA process was varied from 0.165 kW·h·m−3 CH4 to 0.649 kW·h·m−3 CH4. Finally, a dual-stage VPSA process has been successfully developed to upgrade a low concentration coalbed methane containing 20% methane to a target product gas with methane purity higher than 90%, meanwhile the total methane recovery was up to 98.71% with a total energy consumption of 0.504 kW·h·m−3 CH4.

Determining the optimal location and capacity of energy storage systems (ESS) is a crucial planning problem for the virtual power plant (VPP). However, the trading characteristics of VPP have not been considered in the existing ESS optimal planning research due to its complicated mathematical relationships. In this paper, considering the VPP trading environment, a bi-level optimization model is established to determine ESS’s optimal location and capacity. The proposed model is a mixed-integer, nonlinear, multi-period, and large-scale optimal problem, which is difficult to solve directly by traditional methods. Usually, linearizing or decomposing methods are used to simplify the original problem for solving. However, the available simplification methods greatly change the original problem, resulting in a large deviation between the simplified and the original problems. This paper proposes a novel interactive solution framework for the bi-level model based on the decomposition-coordination algorithm for improving the solution accuracy. The simulation results show the effectiveness of the ESS planning scheme in VPP under different objectives, EVs types, and electricity prices. Further analyses based on the IEEE 17-bus VPP system demonstrate that the proposed method can save nearly 29.01%, 28.08%, 26.62% of the ESS cost on average compared with the loss sensitivity factor, MILP-Based, and Benders decomposition methods, respectively.

Let R be a ring such that ( GP , GP ⊥ ) forms a cotorsion pair cogenerated by a set, where GP denotes the category of all Gorenstein projective R-modules. Recently, the first author defined for any complex X the relative cohomology functors Ext GP ⁎ ( X , − ) as H − ⁎ ( Hom ( G , − ) ) in which G is a special Gorenstein projective precover of X. In the present paper, we introduce the dimension of X related to Gorenstein projective precovers, and show that such a dimension of X is equal to the least integer n for which Ext GP i ( X , Q ) = 0 for all i > n and all R-modules Q ∈ GP ⊥ . This result gives a “Gorenstein” version of the relationship between the projective dimension of complexes introduced by Avramov and Foxby and the absolutely cohomology functors Ext R ⁎ ( − , − ) .

Lithium (Li) concentration-dependent mechanical properties are crucial to the performance and durability of lithium ion batteries. Here, we report an in situ measurement of the evolution of elastic modulus and partial molar volume of commercial graphite electrodes. A bending model is developed to analyze the relationship between large curvature changes and materials properties. The curvature changes of the electrode are captured using a CCD camera during electrochemical cycling. Composite graphite electrodes with different thickness ratios are chosen as the working electrode. The modulus and partial molar volume are extracted which are both associated with the stress evolution of electrodes. The results show that the elastic modulus increases during the second lithiation process, while the partial molar volume shows a stage change corresponding to the phase change of graphite materials. These results are important for the mechanical modeling and provide basic information for the commercial graphite electrodes.

Recently, the system parameters of Cygnus X-1, i.e., the black hole mass M, the orbital inclination i and the source distance D, have been updated. As the input constraints of the continuum-fitting method, it is necessary to refine the spin with these new parameters. The Hard X-ray Modulation Telescope (HXMT, also named Insight) was successfully launched on June 15th, 2017 in China. In this work, we analyzed spectra obtained by the Insight-HXMT during 2017-2018 and re-estimated the spin via the continuum-fitting method. We first re-estimated the spin using old parameters and found the dimensionless spin parameter to be a ⁎ > 0.934 (3σ), which is consistent with previous measurements both from the continuum-fitting and iron-line fitting methods ( Gou et al. 2011 , Gou et al. 2014 ; Fabian et al. 2012 , Walton et al. 2016 , Tomsick et al. 2018 ). Then, when the new parameters were applied, we obtained an increased spin: a ⁎ > 0.967 (3σ), which is also consistent with the recent measurement (Zhao et al. 2020, submitted to ApJ) and also confirms an extreme Kerr black hole lying in this system.

Although electrospinning of nanofibrous scaffolds benefit to wound healing have been developed at a fast pace, achieving nanofibrous scaffolds with high absorptivity by green electrospinning and crosslinking techniques is still a great challenge. Here, we developed a maleilated hyaluronate/methacrylated poly (vinyl alcohol) (MHA) (MaPVA) composite nanofibers by electrospinning from pure water solvent and followed by photopolymerization to form crosslinking nanofibers network. Electrospinnability of MHA/MaPVA blend systems were investigated and the results shows that the morphology and diameter of the nanofibers were mainly affected by MHA/MaPVA weight ratios by changing viscosity and conductivity of the blend solutions. The crystalline microstructure of the electrospun fibers was not well developed due to intermolecular hydrogen bonding interaction between the molecules of MHA and MaPVA. The photocrosslinking MHA/MaPVA nanofibrous mats can swell to form fibrous hydrogels with high water absorption, meanwhile it is cytocompatible and capable of promoting the cell attachment, which render it great potential for wound dressings.

In this paper, a model of activated carbon was established by molecular simulation and the separation performance of N2 and CH4 on activated carbon was studied. In order to evaluate the adsorption selectivity and diffusion selectivity of N2 and CH4, Grand Canonical Monte Carlo and molecular dynamic methods were used to obtain equilibrium adsorption isotherms and mean square displacements of N2 and CH4 on activated carbon with different pore sizes. Research results showed that the difference in adsorption isosteric heat of N2 and CH4 at the pore size of 0.46 nm is the largest, which is 5.759 and 7.03 kcal·mol−1 (1 cal=4.184 J), respectively. Activated carbon with pore size of 0.46 nm has the best N2 and CH4 adsorption selectivity, while its diffusion selectivity is not obvious.

Considering the influence of economies of scale and ship capacity on empty container repositioning, using foldable containers and container leasing may be effective ways to save the operating costs of liner shipping companies. Considering the minimization of the transportation costs of empty and laden containers, this paper studies a liner shipping hub location problem with empty container repositioning (LSHLPECR) considering foldable containers. We propose a mixed integer linear program (MILP) for the formulation of the LSHLPECR. In terms of the optimal solution of our MILP, this paper further explores the container leasing pricing problem (CLPP), where our aim is to obtain perceived container leasing prices (PCLPs) utilizing the inverse optimization technique. Numerical experiments verify the effectiveness of the studied problems.