Objective: To analyze three reconstruction techniques and mid-term clinical outcomes of hip revision for acetabular bone defect after total hip arthroplasty (THA). Methods: This is a retrospective case series study. Included in the study were 109 patients (109 hips) with acetabular bone defect after THA reconstructions in hip revisions from January 2015 to December 2021 in the Senior Department of Orthopaedics, the Forth Medical Center of Chinese People's Liberation Army General Hospital and the Department of Orthopaedics, the First Medical Center of Chinese People's Liberation Army General Hospital. According to the preoperative simulated surgeries and different bone defect reconstruction techniques, patients were divided into a normal cup group, an augment group or a triflange group,respectively. There were 54 patients (54 hips) in the normal cup group, reconstructed with the uncemented porous metal cup (including Jumbo cup), with 23 males and 31 females, aged (59.6±9.9) years (range:32 to 76 years); 44 patients (44 hips) in the augment group, reconstructed with the individualized three-dimensional (3D) printed porous metal augment and uncemented porous metal cup, with 18 males and 26 females, aged (52.8±13.6) years(range:17 to 76 years); 11 patients (11 hips) in the triflange group, reconstructed by the individualized 3D printed porous metal triflange cup, with 5 males and 6 females, aged (59.4±11.2) years (range: 43 to 78 years). Radiographic results, including rotation center height, rotation center offset, and leg length discrepancy (LLD) and clinical results, including Harris hip score (HHS) and visual analogue scale(VAS) were evaluated outpatient at 3, 6, 12 months after the operation and annually thereafter. The last follow-up was completed in March 2024, and all parameters at the last follow-up and before the operation were compared. Paired sample t test and repeated measurement ANOVA were used for the radiographic and clinical parameters before and after the operation. Results: All hip revisions for patients with acetabular bone defect after THA were completed and followed for more than two years. The follow-up time of the normal cup group was (6.5±1.7) years (range: 2.8 to 9.3 years), and that of the augment group was (6.0±1.3) years (range: 3.5 to 9.0 years). The follow-up time of the triflange group was (2.8±0.6) years (range: 2.0 to 3.8 years). At the last follow-up, the rotation center height, rotation center offset and LLD of 54 hips in the normal cup group were (24.2±5.6) mm, (29.1±5.5) mm and (4.6±3.3) mm, respectively, and the rotation center height and LLD were significantly lower than those of the preoperative hips (t=9.671, P<0.01; t=6.073, P<0.01). In the augment group, the rotational center height, the rotation center offset and the LLD of 44 hips were (22.4±9.0) mm, (25.4±5.5) mm and (6.0±4.0) mm, respectively, which were significantly lower than those of the preoperative hips (t=9.071, P<0.01; t=11.345, P<0.01; t=4.927, P<0.01). In the triflange group, the rotational center height, the rotation center offset and LLD of 11 hips were (22.7±6.0) mm,(30.9±8.0) mm and (5.3±2.2) mm, respectively, and the rotation center height and LLD were significantly lower than those of the preoperative hips (t=2.716, P=0.022; t=6.226, P<0.01). At the last follow-up, fractures occurred in 3 patients and dislocation occurred in 1 patient in the normal cup group, and fracture reduction and closed reduction were administered under anesthesia, respectively. In the augment group, dislocation occurred in 1 patient and open reduction under anesthesia was performed. The HHS and VAS of the three groups improved significantly after surgery and the differences were statistically significant (all P<0.01). There was no complication in the triflange group. The X-ray at the last follow-up showed that all prostheses and augments were in stable positions and no loosening or migration was observed. Conclusions: For patients with acetabular bone defect after THA undergoing hip revisions, preoperative surgical simulation and rehearsal could help surgeons choose convenient and efficient reconstruction techniques. The targeted selection of Jumbo cup, individualized 3D printed metal augment, and customized triflange cup could achieve satisfactory clinical outcomes.

As a dual-functional catalyst for the hydrogen evolution reaction (HER) and the oxygen evolution reaction (OER), Ru clusters have great potential, but there are certain difficulties regarding their stability on the substrate and the tunability of their electronic environment. Here, the S doped graphited biochar aerogel electrocatalyst was designed and synthesized using terrestrial lignin and algal polysaccharide as a carbon substrate. The Ru clusters were anchored on the S-doped carbon aerogel (P-Ru/SC) by carefully designing the Ru-S bond via a novel plasma assisted high temperature carbonization treatment. The optimized P-Ru/SC-2 catalyst exhibits excellent electrocatalytic performance for the HER and OER, achieving ultra-small overpotentials of 119.6 mV and 193.4 mV at 10 mA cm-2. The dual-electrode requires only 1.47 V to reach 10 mA cm-2. It is worth noting that a large number of S sites on graphited carbon can strongly interact with the Ru clusters, significantly improving the catalytic activity and stability for the HER and OER. The Ru clusters were immobilized onto the S-doped carbon aerogel through a novel plasma-assisted high-temperature carbonization treatment, exhibiting exceptional performance in water splitting.

The widespread application of implantable materials has brought about a corresponding increase in implant-related complications, with implant-associated infections being the most critical. Biofilms, which often form on these implants, can significantly impede the effectiveness of traditional antibiotic therapies. Therefore, strategies such as surgical removal of infected implants and prolonged antibiotic treatment have been acknowledged as effective measures to eradicate these infections. However,the challenges of antibiotic resistance and biofilm persistence often result in recurrent or hard-to-control infections, posing severe health threats to patients. Recent studies suggest that phages, a type of virus, can directly eliminate pathogenic bacteria and degrade biofilms. Furthermore, clinical trials have demonstrated promising therapeutic results with the combined use of phages and antibiotics. Consequently, this innovative therapy holds significant potential as an effective solution for managing implant-associated infections. This paper rigorously investigates and evaluates the potential value of phage therapy in addressing orthopedic implant-associated infections, based on a comprehensive review of relevant scientific literature.

Fenton/Fenton-like reactions have promising implications in biomedicine and environment-related re -mediation. However, their applications are still limited because of incomplete light utilization, low energy -conversion efficiency, and inefficient H2O2 utilization. Herein, near infrared (NIR) light absorbance and photothermal conversion were utilized for H2O2 activation to achieve 4-chlorophenol (4-CP) elimination from water by using a typical doped copper sulfide (Cu2-xS) semiconductor developed via a hydrothermal method. The obtained CuS is not only an attractive Fenton-like agent but also exhibits efficient photo -thermal conversion performance in the NIR spectral range, which broadens the use of the solar spectrum and is beneficial to the photothermal-enhanced Fenton-like degradation process. As expected, by irradiating with an NIR laser (1064 nm), the CuS exhibits excellent NIR absorption capacity and produces hyperpyrexia above 50 celcius. Importantly, the photothermal effects of the CuS nanosheets significantly enhanced the yield of the Fenton-like reaction by accelerating the generation and diffusion of free radicals (h+, center dot O2-, 1O2, and especially center dot OH), which enabled the key mechanism for pollutant degradation. In addition, CuS nanosheets exhibited good stability during the degradation of 4-CP, with low metal-ion leakage and a broad pH range applicability, and the degradation rate was hardly affected by laser power, catalyst concentration, and the presence of metal ions. These results demonstrate the strong potential of the photothermal-enhanced Fenton-like effect in pollutant degradation and propose a promising strategy for environmental remediation with the effective utilization of solar energy.(c) 2023 Elsevier B.V. All rights reserved.

In order to achieve the goal of intelligent management of wastewater treatment plants, it is necessary to monitor the parameters of wastewater treatment in real time. Currently, soft measurement technology based on neural network is widely used to solve the problem of key parameters that are difficult to obtain directly in wastewater treatment processes. Selecting appropriate input variables can reduce the complexity of the neural network topology while improving the prediction accuracy of the soft measurement model. To this end, this paper proposes a variable selection method based on the filter-wrapped hybrid framework (FWHVS), which uses the maximum information coefficient (MIC) index and a radial basis function (RBF) neural network. The proposed method only considers removing redundant and irrelevant variables to optimize the review stage of the SFFS method, thus improving computational efficiency. Finally, common variable selection methods are used as comparison methods to verify the effectiveness of the proposed method using the UCI wastewater treatment dataset.

The health and environmental problems caused by volatile organic compounds (VOCs) have attracted wide attention. Photocatalytic technology provides a green and sustainable way for VOCs removal. How to build a highly efficient and stable photocatalyst is of great significance to promote the practical application of photocatalysis technology. In this review, the literatures on photocatalytic oxidation in VOCs are surveyed and systematically categorized based on the types of photocatalytic materials. The methods of improving photocatalytic activity are studied, and the deactivation process of photocatalyst is discussed. Finally, the reaction mechanism is summarized according to the charge separation process and the classification of reactive oxygen species.

Rational surface engineering of noble metal-doped photocatalysts is essential for the efficient conversion of solar energy into chemical energy, but it is still challenging to perform. Herein, we reported an effective strategy for structuring alloyed CuPd (CP) nanoclusters on the ordered mesoporous TiO2 (CPT) by a pore confinement effect. The resultant CPT exhibited an extraordinary photocatalytic activity during Stille reaction under visible light. The X-ray photoelectron spectroscopy spectra, the field emission scanning electron microscope (FESEM) images, and the aberration-corrected high-angle annular dark scanning transmission electron microscopy (HAADF-STEM) images demonstrated that CP nanoclusters were anchored in the mesoporous pore wall of TiO2, and the atomic ratio as well as densities of CP could be precisely modulated via the coordination configuration. As the atomic ratio of CP to TiO2 increased to a certain extent, their photocatalytic activity during Stille reaction increased. A mechanistic investigation suggested that the CP alloy could absorb visible light and its conduction electrons gained energy, which were available at the surface Pd sites. This allowed the Pd sites to become electron-rich and to accelerate the rate-determining step of the Stille reaction. As a result, the efficiency of the photocatalytic Stille coupling reaction was extraordinary enhanced.

Periprosthetic joint infection (PJI) involves complex immunomodulatory interactions between pathogens,biomaterials,and hosts,and correlates with alterations in the ratio of immune cells as well as in the concentration of immune checkpoint molecules.Prosthesis,biofilm,microorganisms,and host constitute a special and complex immune microenvironment.Fully studying the characteristics of immune microenvironment and potential targets of immunotherapy in orthopedic implant-associated infections are expected to provide a new direction for clinical treatment of PJI. An overview of the literature related to PJI and immune regulation at domestic and international sites was conducted to summarize and analyze the characteristics of the immune microenvironment and the potential value of related immunotherapy, aiming to provide new insights for the targeted treatment of PJI.

A flexible CuS/Matrimid composite membrane with tunable near-infrared absorption is constructed. The composite membrane exhibits good near-infrared light-driven photothermal vapor evaporation and seawater desalination effects.

For wastewater treatment plants, a large number of process variables are demanded to monitor the operation of the system. Given the problem that some key water quality variables are difficult to get in real-time, a soft-sensor technology is devised to get the value of these variables. For a soft-sensor model, choosing the appropriate input variables will have a great impact on its performance. In this paper, automatic relevance determination (ARD) method which based on Gaussian process regression (GPR) is proposed to select the appropriate input variables. The ARD method considers the nonlinear mapping relationship from input variables to the output variable. Moreover, the wastewater treatment plant is modeled by GPR, which requires fewer model parameters and can give a confidence interval. Finally, an example of the wastewater treatment plant is used to prove the effectiveness of the method.

High-dimensional data are widely present in machine learning tasks, and various dimensionality reduction methods have emerged to improve model training speed and avoid dimensionality catastrophe. Filter-based feature selection methods are favored for their fast processing speed and lack of dependence on model structure. A filtered feature selection method that combines the maximum information coefficient (MIC) with the feature selection framework of redundancy coefficient gradual up (RCGU) is proposed, and the attention mechanism is introduced into it. The method is verified to be effective in eliminating irrelevant variables and reducing redundant variables through Friedman numerical experiment. Finally, the proposed method is successfully applied to the selection of auxiliary variables for the soft measurement model used in a wastewater treatment plant, and the variables selected by this method improve prediction performance of the model in comparison with other feature selection methods.

The wastewater treatment plant that operates abnormally may lead to poor effluent quality, resulting in the destruction of the environment, and even more serious situation. Therefore, it is necessary to detect and isolate faults in the wastewater treatment plants. This paper proposed a method of fault detection and isolation using interval model. Radial basis function (RBF) neural network is utilized to model the wastewater treatment plant, and the linear output weights of the neural network are estimated by the set membership identification algorithm. After that, the confidence interval of the predicted effluent variables can be obtained, and then the interval boundary is used as the threshold for fault detection. After detecting the fault, based on this interval model and the Bayesian reasoning, the posterior probability of the considered faults can be calculated. When the probability in exceed of a certain threshold, the fault can be successfully isolated. The final experimental results verified the method.

The gas–water interface plays an important role in the photocatalytic degradation of volatile organic compounds (VOCs). Herein, a novel photocatalytic reactor with a tunable gas–water interface was...

污水处理厂配备许多传感器用于监测出水水质.传感器的正常工作与否对保证出水水质至关重要.给出了一种污水处理出水变量传感器故障检测方法.该方法根据入水和出水数据,采用径向基函数神经网络构造出水变量预测模型;使用参数线性集员辨识算法得到网络输出权值的集合描述,从而使预测模型能够给出出水变量的置信区间;以此置信区间为基础获得传感器的故障检测策略.由于置信区间描述了出水变量的存在范围,当传感器测量值超出置信区间,则可推断传感器发生故障.此外,在设计传感器故障检测策略时还考虑了污水处理过程异常的影响.实验结果证实所提方法的有效性.

In wastewater treatment processes, the monitoring of dissolved oxygen sensor is the key to ensure the quality of effluent. In this paper, a method for fault detection of dissolved oxygen sensor is proposed using set membership identification and radial basis function(RBF) neural network. The time series model of KLa5 is built by RBF neural network in virtue of its universal approximation ability. Considering the bounded modeling error, the set description of the output weights of the network is obtained by linear-in-parameters set membership identification algorithm. This built model can give a one-step prediction of the confidence interval of KLa5 under the fault-free case. If the real of KLa5 exceeds the predicted confidence interval, a failure of the dissolved oxygen sensor can be determined.

Electromagnetic coupled resonant wireless power transfer (WPT) technology can realize the soft connection of energy and has received extensive attention in recent years. To reduce the volume of the device and further improve the operating frequency and efficiency of the system, this paper proposed to build a high-frequency WPT using silicon carbide (SiC) MOSFET. Based on the two-port network and the T-model equivalent circuit, the mathematical model of the resonant circuit is obtained. The transmission characteristics of series–series (SS), double-sided LCL and double-sided LCC resonant circuits are analyzed at high-frequency. The studies show that under the same circuit parameters, the double-sided LCC resonant circuit has a stronger carrying capacity while maintaining high transmission efficiency, which solves the problem of the small transmission power of double-sided LCL. Finally, a double-sided LCC type WPT experimental prototype with an operating frequency of 600kHz, an input voltage of 48V, an input power of 600W and transmission efficiency of ≥ 90% was built. Which provides a reference for the design of high-frequency WPT and the analysis of resonant circuits.

Objective: To prospectively evaluate the efficacy of a neurosurgical enhanced recovery after surgery (ERAS) protocol on the management of postoperative pain after elective craniotomies. Methods: This randomized controlled trial was conducted in the neurosurgical center of Tangdu Hospital (Fourth Military Medical University, Xi'an, China). A total of 129 patients undergoing craniotomies between October 2016 and July 2017 were enrolled in a randomized clinical trial comparing an ERAS protocol to a conventional postoperative care regimen. The primary outcome was the postoperative pain score assessed by a verbal numerical rating scale (NRS). Results: Patients in the ERAS group had a significant reduction in their postoperative pain scores on POD 1 compared to patients in the control group (p < 0.05). More patients (n = 44, 68.8%) in the ERAS group experienced mild pain (NRS: 1 to 3) on POD1 compared with patients (n = 23, 35.4%) in the control group (p < 0.05). A further reduction in pain scores was also observed on POD 2 and maintained on POD 3 in the ERAS group compared with that in the control group. In addition, the median postoperative length of hospital stay was significantly decreased with the incorporation of the ERAS protocol compared to controls (ERAS: 4 days, control: 7 days, P<0.001). Conclusion: The implementation of a neurosurgical ERAS protocol for elective craniotomy patients has significant benefits in alleviating postoperative pain and enhancing recovery leading to early discharge after surgery compared to conventional care. Further evaluation of this protocol in larger, multi-center studies is warranted.

CuO/CeO2 mesoporous nanosheets exhibited superior soot oxidation activity owing to the synergistic effects.

In view of the difficulty of real-time measurement of the effluent total phosphorus (TP) for a wastewater treatment plant (WWTP), in this paper, a new TP soft sensor which is different from the traditional single value method is presented. It realizes the guaranteed estimation of the TP concentration by predicting the upper and lower bounds. Partial least squares is used to obtain the secondary variables of the effluent TP. Then, an input-output model with secondary variables as the inputs and the effluent TP as the output is built by the radial basis function neural network (RBFNN). Considering the bounded modeling error, the linear-in-parameter set membership identification algorithm is used to obtain a description of the uncertain set of the output weights of the RBFNN. During the operation of the WWTP, the established soft sensor can predict the upper and lower bounds of the effluent TP concentration. Besides, a bundle of soft sensors is constructed and the intersection of the results given by the soft sensors is used to reduce the conservativeness caused by using a single sensor. The experimental results show the effectiveness of the proposed method.

To achieve efficient operation of the wastewater treatment plant(WWTP), it is necessary to establish a model that accurately describes the behavior of the plan. In this paper, the radial basis function neural network (RBFNN) is utilized in the modeling of the WWTP basing on the available influent and effluent data. Considering the bounded modeling error, linear-in-parameters set membership identification algorithm is used to describe an uncertain set of each vector representing the weights of the links between all the hidden neurons and one output neuron. Comparing with the existing methods which are all proposed for a single effluent variable, the method here builds a predictor model which can compute confidence intervals for multiple effluent variables simultaneously according to the values of the influent variables. The confidence intervals can characterize the existence ranges of the effluent variables, such that reliable estimates of them are obtained. By the estimates, the effluent quality or the WWTP performance can be evaluated. Besides, the interval predictor model is also applied to the fault detection and isolation of the WWTP to realize reliable operation. The experiment results show the satisfying performance of the proposed method.