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Bolted connection is one of the most widely used connection forms in various mechanical structures. However, the discretization of preload during tightening will be aggravated by the presence of geometric error caused by manufacturing. In this work, the geometric error transmitted by all parts of the bolted joint is equated to the existence of a certain wedge angle between the nut and the bearing surface of the connected part, that is, the nut and the bearing surface are in non-parallel contact. A torque-preload mathematical equation is theoretically established to account for non-parallel contact. On this basis, the relation between torque and preload deviation is considered to analyze the formation mechanism of preload deviation according to non-parallel contact. Subsequently, the influence of non-parallel contact on tightening performance was quantitatively analyzed by experiments and finite element. The analysis results showed that the tightening process under non-parallel contact can be divided into two stages: nonlinear increase stage and linear increase stage. Among them, the deviation mainly appears in the first stage. Tightening performance analysis herein is helpful to reduce the influence of geometric error on the preload control and further improve its reliability.

Wildfires generate abundant smoke primarily composed of fine-mode aerosols. However, accurately measuring the fine-mode aerosol optical depth (fAOD) is highly uncertain in most existing satellite-based aerosol products. Deep learning offers promise for inferring fAOD, but little has been done using multiangle satellite data. We developed an innovative angle-dependent deep-learning model (ADLM) that accounts for angular diversity in dual-angle observations. The model captures aerosol properties observed from dual angles in the contiguous United States and explores the potential of Greenhouse gases Observing Satellite-2’s (GOSAT-2) measurements to retrieve fAOD at a 460 m spatial resolution. The ADLM demonstrates a strong performance through rigorous validation against ground-based data, revealing small biases. By comparison, the official fAOD product from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Visible Infrared Imaging Radiometer Suite (VIIRS), and the Multiangle Imaging Spectroradiometer (MISR) during wildfire events is underestimated by more than 40% over western USA. This leads to significant differences in estimates of aerosol radiative forcing (ARF) from wildfires. The ADLM shows more than 20% stronger ARF than the MODIS, VIIRS, and MISR estimates, highlighting a greater impact of wildfire fAOD on Earth’s energy balance.

Fine-mode aerosol optical depth (fAOD) is a vital proxy for the concentration of anthropogenic aerosols in the atmosphere. Currently, the limited data length and high uncertainty of the satellite-based data diminish the applicability of fAOD for climate research. Here, we propose a novel pretrained deep learning framework that can extract information underlying each satellite pixel and use it to create new latent features that can be employed for improving retrieval accuracy in regions without in situ data. With the proposed model, we developed a new global fAOD (at 0.5 μm) data from 2001 to 2020, resulting in a 10% improvement in the overall correlation coefficient (R) during site-based independent validation and a 15% enhancement in non-AERONET site areas validation. Over the past two decades, there has been a noticeable downward trend in global fAOD (−1.39 × 10–3/year). Compared to the general deep-learning model, our method reduces the global trend’s previously overestimated magnitude by 7% per year. China has experienced the most significant decline (−5.07 × 10–3/year), which is 3 times greater than the global trend. Conversely, India has shown a significant increase (7.86 × 10–4/year). This study bridges the gap between sparse in situ observations and abundant satellite measurements, thereby improving predictive models for global patterns of fAOD and other climate factors.

A 1200-V rated CoolSiC Trench MOSFET structure has excellent overall electrical characteristics due to its unique asymmetric structure. However, it is sensitive to space heavy ion radiation. In this study, heavy ion irradiation experiments were conducted on 1.2 kV CoolSiC Trench MOSFET devices to calibrate the simulation structure model and critical failure conditions. The 2-D numerical simulator SILVACO TCAD was used to investigate the single event burnout (SEB) hardening method for the 1.2 kV-rated CoolSiC Trench MOSFET under high linear energy transfer (LET) values. The simulation results show that the improved CoolSiC Trench MOSFET structure can effectively enhance the SEB capability of the device without sacrificing its excellent overall electrical characteristics compared to the traditional CoolSiC Trench MOSFET. At 360 V voltage and 0.5 pC/ $\mu $ m LET value, the highest temperature is reduced from 3097 to 1502 K, and the lowest burnout threshold is increased by 200 V in the improved structure while maintaining almost unchanged characteristics at other locations.

AbstractIn the case of a new nuclear reactor, existing evaluation experience is limited; thus, accidents and troubles may occur as a result of such lack of experience. To deal with such situations, it is desirable to use a virtual nuclear plant to reproduce behaviors under various conditions and identify unknown anomalies from the behaviors. Then, when an abnormal situation occurs, one can quickly determine the cause of the abnormality to operate plant equipment and return the plant to a stable condition as quickly as possible. Two types of deep neural network (DNN) systems have been constructed to support the identification of unknown anomalies and the determination of their causes. One is a surrogate system that can estimate physical quantities of a nuclear power plant in a computational time of several orders less than a physical simulation model. The other is an abnormal situation identification system that can estimate the state of the disturbance causing an anomaly from physical quantities of a nuclear power plant. Both systems are trained and tested using data obtained from the analytical code for incore and plant dynamics (ACCORD), which reproduces the steady and dynamic behavior of the actual High Temperature Engineering Test Reactor (HTTR) under various scenarios. The DNN models are built by adjusting the main hyperparameters. Through these procedures, these systems are shown to be able to perform with a high degree of accuracy.

The Bolted joint loosening is challenging to describe with an accurate mathematical model. Therefore, a prediction model of bolted joint loosening was proposed based on a deep learning network. Firstly, the loosening experiments of the bolted joint were carried out with an orthogonal test. And the nonlinear and uncertain characteristics of bolted joint loosening process were further analyzed. Furthermore, a prediction model of bolted joint loosening based on a deep learning network was established. The proposed model was trained and verified using the experimental data. The results showed that compared with the traditional mathematical and regression models, the model could not only obtain the change of the mean value of preload but also describe the confidence interval of the change of preload in the sense of probability synchronously. The experiment data and prediction data are in good agreement, which can be used to validate the rationality of the model.

Epigenetic modifications of chromatin, including histone acetylation, and tumor angiogenesis play pivotal roles in creating an immunosuppressive tumor microenvironment. In the randomized phase 2 CAPability-01 trial, we investigated the potential efficacy of combining the programmed cell death protein-1 (PD-1) monoclonal antibody sintilimab with the histone deacetylase inhibitor (HDACi) chidamide with or without the anti-vascular endothelial growth factor (VEGF) monoclonal antibody bevacizumab in patients with unresectable chemotherapy-refractory locally advanced or metastatic microsatellite stable/proficient mismatch repair (MSS/pMMR) colorectal cancer. Forty-eight patients were randomly assigned to either the doublet arm (sintilimab and chidamide, n= 23) or the triplet arm (sintilimab, chidamide and bevacizumab, n= 25). The primary endpoint of progression-free survival (PFS) rate at 18 weeks (18wPFS rate) was met with a rate of 43.8% (21 of 48) for the entire study population. Secondary endpoint results include a median PFS of 3.7 months, an overall response rate of 29.2% (14 of 48), a disease control rate of 56.3% (27 of 48) and a median duration of response of 12.0 months. The secondary endpoint of median overall survival time was not mature. The triplet arm exhibited significantly improved outcomes compared to the doublet arm, with a greater 18wPFS rate (64.0% versus 21.7%, P= 0.003), higher overall response rate (44.0% versus 13.0%, P= 0.027) and longer median PFS rate (7.3 months versus 1.5 months, P= 0.006). The most common treatment-emergent adverse events observed in both the triplet and doublet arms included proteinuria, thrombocytopenia, neutropenia, anemia, leukopenia and diarrhea. There were two treatment-related fatalities (hepatic failure and pneumonitis). Analysis of bulk RNA sequencing data from the patients suggested that the triplet combination enhanced CD8+T cell infiltration, resulting in a more immunologically active tumor microenvironment. Our study suggests that the combination of a PD-1 antibody, an HDACi, and a VEGF antibody could be a promising treatment regimen for patients with MSS/pMMR advanced colorectal cancer. ClinicalTrials.gov registration: NCT04724239.

To evaluate the effect of acupuncture on anisometropic amblyopia (AA) and explore its potential mechanism for children with AA.

Byline: Xing-Chang. Yan, Ming. Liu, Pei-Pei. Li, Xiao-Tong. Guo, Yu-Jun. Xu, Xiang-Meng. He, Cheng-Li. Li Objective: This study sought to establish the diagnostic utility of performing a second biopsy using [...]

Wide applications of diazonium salts (DS) are limited due to their nature of poor thermal stability and explosive hazards. In this work, strong acid cation-exchange resin (Amberlyst-15), as an acid and anion provider, was used to synthesize the corresponding diazonium salt of weakly basic p-nitroaniline (p-NA). The thermal stability of raw materials (p-nitroaniline, Amberlyst 15) and cation-exchange resin-supported DS (CER-supported DS) was characterized by DSC and ARC, respectively. The synthesis conditions were optimized, and the exothermicity of the diazotization reaction was characterized by reaction calorimetry. Diazonium salts of p-NA were demonstrated to be obtained and chemisorbed on the cation-exchange resin surface. The optimal yield of CER-supported DS reached up to 80%. The initial decomposition temperature and decomposition energy of the CER-supported DS were about 55 °C and 183 J/g, respectively. The decomposition process of the CER-supported DS followed a single n-order reaction model, and the main decomposition product was p-nitrophenol. The merits of this synthesis method include being free of environmentally harmful inorganic acids and high-cost of tert-butyl nitrites and having good storage stability.

Hydrofoils, as the actuators in hydrofoil attitude control systems (HACSs), are prone to faults and failures resulting in fatal accidents. In this article, a fault detection and estimation (FDE) strategy for such failures is presented based on a developed baseline model. The actuator fault is first parameterized by rewriting the dynamic model of the HACS. To address non-Gaussian factors in the joint estimation of the unscented Kalman filter (UKF), the Gaussian mixture model (GMM) is then integrated with the conventional UKF to approximate the complex distributions. Considering the problem of singular or ill-conditioned covariance matrices in the GMM, a covariance regularization approach based on the posterior estimation with the inverse-Wishart distribution is explored. Actuator anomalies can be detected via a scale metric utilizing the covariance matrices, together with the peak signal-to-noise ratio (PSNR) index, and accurate fault estimation is implemented by isolating fault information from the augmented state even in the presence of non-Gaussian disturbances. The effectiveness of the proposed strategy is validated by the experiment carried out on a hardware-in-loop (HIL) platform. The RMSE results for fault estimation obtained through the method proposed in this article exhibit the reductions of 19.23% and 31.77% for the constant-value fault scenario, 5.03% and 16.31% for the time-varying fault mode, when compared with the results obtained using the joint UKF and the Bayesian-based adaptive Kalman filter with Gaussian-inverse-Wishart mixture (BAKF-GIWM) techniques. These findings underscore the superior efficacy and performance of the proposed method.

A series of nano-WC surface modified AlSi10Mg powders with different WC contentswere synthesized by the electrostatic assembly method. After the selective laser melting (SLM) processing, various Al−W intermetallicswere in-situ formed in the SLM nano-WC/AlSi10Mg composites. A well-coherent Al/Al5W interface with a low lattice mismatch of 4.7% was confirmed with an orientation relationship of (002)α(Al)//(104)Al5W. The nano-WC particles and Al−W intermetallics triggeredthe columnar-to-equiaxed transition, leading to a fine equiaxed microstructure. As a result, the SLMed 3 wt.% nano-WC/AlSi10Mg composites showed remarkable mechanical properties, with an ultimate tensile strength of (464.1±8.68) MPa and elongation of (5.6±0.95)%. Additionally, the SLMed 3 wt.% WC/AlSi10Mg samples also achieved the lowest average coefficient of friction (0.429) and wear rate of 3.842×10−5mm3/(N·m) compared to other WC/AlSi10Mg composites. The remarkable mechanical and wear properties are ascribed to fine-grain and second-phase strengthening.

Coarse-mode aerosol optical depths (cAODs) are critical for understanding the impact of coarse particle sizes, especially dust aerosols, on climate. Currently, the limited data length and high uncertainty of satellite products diminish the applicability of cAOD for climate research. Here, we propose a spatiotemporal coaction deep-learning model (SCAM) for the retrieval of global land cAOD (500 nm) from 2001–2021. In contrast to conventional deep-learning models, the SCAM considers the impacts of spatiotemporal feature interactions and can simultaneously describe linear and nonlinear relationships for retrievals. Based on these unique characteristics, the SCAM considerably improved global daily cAOD accuracies and coverages (R = 0.82, root-mean-square error [RMSE] = 0.04). Compared to official products from the multiangle imaging spectroradiometer (MISR), the moderate resolution imaging spectroradiometer (MODIS), and the polarization and directionality of Earth’s reflectances (POLDER) instrument, as well as the physical-deep learning (Phy-DL) derived cAOD, the SCAM cAOD improved the monthly R from 0.44 to 0.88 and more accurately captured over the desert regions. Based on the SCAM cAOD, daily dust cases decreased over the Sahara, Thar Desert, Gobi Desert, and Middle East during 2001–2021 (>3 × 10–3/year). The SCAM-retrieved cAOD can contribute considerably to resolving the climate change uncertainty related to coarse-mode aerosols. Our proposed method is highly valuable for reducing uncertainties regarding coarse aerosols and climate interactions.

The effects of different annealing processes on the phase precipitation behavior and corrosion properties of copper-bearing 430 ferritic stainless steel were systematically investigated. The shape, quantity and distribution of copper-rich precipitates by different annealing processes were characterized by scanning electron microscopy, transmission electron microscopy, backscatter electron and backscatter diffraction. The pitting resistance behavior in simulated physiological saline environments (0.9 wt.% NaCl) was investigated using electrochemical workstation and X-ray photoelectron spectroscopy. The results showed that the copper-rich phase prepared by repeated rolling and annealing gradually changed from long needle-like to short thick rod-like and granular, whose distribution tended to be uniform and diffusive, and the number of copper-rich phases increased. After solution/antibacterial annealing process, the size and density of the copper-rich phase increase, resulting in a discontinuity of the passivation film on the stainless steel, which reduces the pitting resistance to some extent. The refinement mechanism revealed that pre-deformation brings about a modification in both precipitation mechanism and growth kinetics of epsilon copper.

We propose a novel, succinct, and effective approach for distribution prediction to quantify uncertainty in machine learning. It incorporates adaptively flexible distribution prediction of $\mathbb {P}(\mathbf {y}|\mathbf {X}=x)$P(y|X=x) in regression tasks. This conditional distribution's quantiles of probability levels spreading the interval (0,1) are boosted by additive models which are designed by us with intuitions and interpretability. We seek an adaptive balance between the structural integrity and the flexibility for $\mathbb {P}(\mathbf {y}|\mathbf {X}=x)$P(y|X=x), while Gaussian assumption results in a lack of flexibility for real data and highly flexible approaches (e.g., estimating the quantiles separately without a distribution structure) inevitably have drawbacks and may not lead to good generalization. This ensemble multi-quantiles approach called EMQ proposed by us is totally data-driven, and can gradually depart from Gaussian and discover the optimal conditional distribution in the boosting. On extensive regression tasks from UCI datasets, we show that EMQ achieves state-of-the-art performance comparing to many recent uncertainty quantification methods. Visualization results further illustrate the necessity and the merits of such an ensemble model.

In this article, a sliding mode control design method is developed for a class of fully nonlinear systems in generalized regular form, where both input distribution uncertainty and system uncertainties are considered. Based on the generalized regular form, a novel nonlinear sliding surface is designed and uniform ultimate stability of the corresponding sliding mode dynamics is analyzed. Then, under the assumption that the uncertainties are bounded by known nonlinear functions of the system states, a sliding mode controller is formulated to ensure that the dynamical system reaches the sliding surface in finite time even in the presence of the system uncertainties and input distribution uncertainties. Further, for the case of system uncertainty with unknown bound in parameterized form, an adaptive sliding mode controller is developed to drive the dynamical system to the sliding surface and maintain a sliding motion thereafter. The developed sliding mode controller is applied to a high incidence research model aircraft model. Simulation results demonstrate that the developed methods are effective.

Increasing the proportion of clean energy is an inevitable trend of high-quality energy development. While enjoying the benefits of clean energy, traditional fossil energy enterprises face great challenges. In this study, coal power and photovoltaic power are selected as examples for analysis. Considering coal consumption, carbon emission, unit ramp conditions and photovoltaic abandonment, a comprehensive income model containing thermal power and photovoltaic power generation is proposed. The objective function of maximizing earnings is established and solved by genetic algorithm. The results show that the overall benefit will increase if the proportion of photovoltaic does not increase blindly. The unreasonable ratio of thermal and photovoltaic power and the imbalance of supply and consumption will lead to the decline of economic benefits and the increase of coal consumption and carbon emission. In the case of a high proportion of clean energy penetration, on the one hand, traditional power plants should be responsible for ensuring the instability of electricity output when the photovoltaic is weak, on the other hand, they need to give up some of the supply proportion when clean power is at a high output state. Therefore, while increasing the proportion of clean energy, it is necessary to improve the speed of load adjustment, the depth of peak regulation and the efficiency of low load work in traditional power plants to ensure the healthy development of new energy.

Lung cancer is one of the most malignant cancers in China with a rising incidence rate. Despite the fact that surgical treatment is the only possible cure for lung cancer, its long-term efficacy is compromised by the high level of postoperative local recurrence rate. Minimal residual disease is the leading cause of tumor recurrence, yet the suggested combination of clinical, radiological and serological (carcinoembryonic antigen) tests fails to reveal the underlying residual tissue in all stage I-III lung cancer cases, which makes tumor recurrence surveillance timely. Through monitoring circulating tumor DNA, the minimal residual disease level can be accessed and provide guidance for more precise postoperative personalized treatment, and its scientific feasibility can revolutionize lung cancer therapy. In the present review we summarized the progress of circulating tumor DNA in lung cancer minimal residual disease detection and discussed its application value in guiding precise treatment of lung cancer.

The successful bid for the 2022 Winter Olympics has provided a strong impetus for the development of China's ski industry. Ski areas have sprung up throughout the country, even in the low latitudes south of 30°N. However, ski tourism is extremely susceptible to weather and climate conditions. In the context of global warming, it has become important to assess the climate reliability of ski areas. Therefore, this study demonstrates a novel approach to assessing the ski tourism sector's climate risks, which can be easily applied in other markets catering to the same industry. Using the random forest regression model based on climate projections and survey data, we projected the ski season start dates, end dates and season lengths of 694 existing ski areas in China under three emission scenarios (RCP2.6, RCP4.5 and RCP8.5). Climate projections, including air temperature, snowfall, rainfall, wind speed and air humidity, were the ensemble means from five climate models. Results indicate that ski areas in China may have later start dates, earlier end dates and shorter ski seasons before 2099. By the 2090s, under RCP2.6, RCP4.5 and RCP8.5, 20% (139), 28% (195) and 35% (245) of ski areas are projected to be at high climate risk (ski season less than 60 d), respectively, while 28% (197), 23% (157) and 8% (56) of ski areas are at low climate risk (ski season with at least 100 d), respectively. The climate risks are ranked from the highest to lowest in East, Central, Southwest, North, Northwest and Northeast China. Furthermore, the ski tourism sector in the latitudes south of 40°N is exposed to much higher climate risks than in areas north of 40°N. Therefore, climatic reliability should be carefully considered before establishing or expanding ski areas to avoid unnecessary resource waste and ecological damage, as well as to promote sustainable development in mountain areas.

Fine-mode aerosol optical depth (fAOD) is related to anthropogenic aerosols, which play an essential role in global climate change and the atmospheric environment. However, knowledge of the global fAOD in the 1990s is very limited. Compared with general satellite-based fAOD retrieval methods, the spectral deconvolution algorithm (SDA) provides an entirely different way to calculate fAOD. In this study, we derived three new SDA-based global daily fAOD ( $0.55\mu \text{m}$ ) datasets from 1995 to 2003 with 1 $^{\circ }\,\,\times1^{\circ }$ spatial resolution using the second Along-Track Scanning Radiometer (ATSR-2) aerosol product data. In global-scale validation, the application of SDA to Swansea University (SU)–ATSR aerosol products for fAOD retrievals showed the best agreement with AErosol RObotic NETwork (AERONET) fAOD, with a correlation coefficient of 0.72, a root-mean-square error (RMSE) of 0.12, and $\sim $ 65.36% of retrievals inside of the estimated error envelope (EE) (±[0.05 + 15%]). Regionally, SDA improves retrieval performance in Southeast Asia and USA when using the SU and ATSR-dual view (ADV) aerosol products. However, the application of SDA to Oxford-RAL Aerosol and Cloud (ORAC)-based aerosol data considerably worsened its accuracy compared with the official ORAC fAOD. With the improved SU–SDA fAOD, the long-term trend showed a considerable decrease in fAOD in Central South America from 1995 to 2003. However, significantly increasing trends were observed in India and China. As SDA uses spectral AOD only, this study demonstrates that it is a promising method for optical satellite spatial fAOD retrieval.

ObjectiveMethionine metabolism is involved in a myriad of cellular functions, including methylation reactions and redox maintenance. Nevertheless, it remains unclear whether methionine metabolism, RNA methylation and antitumour immunity are molecularly intertwined.DesignThe antitumour immunity effect of methionine-restricted diet (MRD) feeding was assessed in murine models. The mechanisms of methionine and YTH domain-containing family protein 1 (YTHDF1) in tumour immune escape were determined in vitro and in vivo. The synergistic effects of MRD or YTHDF1 depletion with PD-1 blockade were also investigated.ResultsWe found that dietary methionine restriction reduced tumour growth and enhanced antitumour immunity by increasing the number and cytotoxicity of tumour-infiltrating CD8+T cells in different mouse models. Mechanistically, the S-adenosylmethionine derived from methionine metabolism promoted the N6-methyladenosine (m6A) methylation and translation of immune checkpoints, including PD-L1 and V-domain Ig suppressor of T cell activation (VISTA), in tumour cells. Furthermore, MRD or m6A-specific binding protein YTHDF1 depletion inhibited tumour growth by restoring the infiltration of CD8+T cells, and synergised with PD-1 blockade for better tumour control. Clinically, YTHDF1 expression correlated with poor prognosis and immunotherapy outcomes for cancer patients.ConclusionsMethionine and YTHDF1 play a critical role in anticancer immunity through regulating the functions of T cells. Targeting methionine metabolism or YTHDF1 could be a potential new strategy for cancer immunotherapy.

In order to reach the ambitious net-zero emission target by 2050, various technological solutions need to be developed to ensure efficient utilisation of energy. Commercial and residential buildings are a big source of greenhouse gas emissions, where efficient utilisation of energy can play a major role towards decarbonisation of the buildings sector.  Heat pumps have recently emerged as an effective solution for space heating applications in buildings. Energy-efficient operation of heat pumps will make a significant contribution toward making buildings energy-efficient. In this context, heat pump control systems have a major role. Some of the existing literature on the heat pump control systems assume that various system states are available to measure. This may not always be true and/or economical to measure all the states. Moreover, the system is subject to various disturbances which cannot be directly measured. To reduce the number of sensors in heat pump control systems, an adaptive observer is developed in this paper to estimate inaccessible system states and disturbances simultaneously. An advantage of the proposed approach is that it does not require any bound on the disturbance itself, however, only assumes that the rate of change of disturbance is bounded. This is always the case in practice. In the developed method, adaptive control techniques and variable structure control techniques are combined to implement the proposed observer. In order to estimate the unknown disturbance, an augmented systems model is considered. Globally uniformly ultimately bounded property of the error dynamical systems is established by suitably designing the adaptive laws. The developed method is applied to a model of the heat dynamics of a house floor heating system connected to a ground source-based heat pump. Different disturbance signals formats and amplitudes are considered to show the effectiveness of the proposed technique. Simulation results are given to demonstrate the suitability of the proposed method.

The mechanical performances such as tensile strength and blast property of metal lined SiC/SiC composite cladding tubes were investigated. Nb or Ta was selected as liner material, and the SiC/SiC composite layer was fabricated by winding and different precursor impregnation and pyrolysis (PIP) processes. The tensile strengths of different tube samples were measured at room temperature (RT) and 1200 °C, respectively. The blast property was investigated through the maximum water pressure of tubes. And the fracture microstructures were observed by SEM. The highest tensile strength at RT was 150.7 MPa. The blast strength was enhanced with the PIP process increasing from 1 to 4 cycles and the tube of 4 PIP cycles had the highest water pressure of 34.7 MPa. Compared with the metal tubes, the multi-layer structure improved tensile and blast properties significantly. The different processes such as PIP cycles and pyrolytic carbon (PyC) coating were important factors to enhance the mechanical performances of SiC/SiC-based tubes. However, the retention rate of tensile strength was only 18.5% at 1200 °C.

Threaded fasteners are one of the most commonly used connection methods for mechanical structures. Its primary function is to generate appropriate clamping forces and fasten the connected parts. An inappropriate preload can cause loosening, fatigue fracture, and other problems. This will affect the safety and reliability of mechanical equipment. The precise control of the preload has become a critical issue in mechanical assembly processes. Over the past few decades, various tightening measures and methods have been proposed to address this issue. However, many problems continue to exist with practical applications that have not been reviewed comprehensively and systematically. First, various control methods were summarized systematically, and their advantages and disadvantages in engineering applications were analyzed. Torque control is the most widely used tightening method owing to its simple operation and low cost. Therefore, the research on the torque control method was summarized systematically from three aspects: the torque–preload correlation formula, effective friction radius, and friction characteristics during tightening. In addition, the special circumstances that may increase preload uncertainty were discussed. Finally, based on a summary of the current research status, the prospects for future research were discussed. This study would aid researchers in extensively understanding the problems in preload control.

AbstractWhen total volume control is applied to toxicity in nuclear waste management it becomes a limiting factor for the permittable total operating capacity of nuclear reactors. An alternative conceptual scenario is proposed, aimed at toxicity reduction through partitioning and transmutation. Specifically, the electricity generation capacity could be increased by transmutation of 90Sr and 137Cs. Simultaneously, the cooling time before disposal is reduced to 50 years from the 300 years required by existing scenarios, such as the accelerator-driven system. Finally, the scenario is also found to be feasible in terms of energy balance and cost, using an Li(d,xn) reaction neutron source with a deuteron accelerator for transmutation.

Background:: To investigate theinvitroinduction of salivary gland-like tissue by ips cells in an interferon regulatory factor 6 (IRF6) overexpression and parotid conditioned medium environment. Methods:: Urine-derived ips cells were isolated, identified, transfected with IRF6 and cultured in parotid conditioned medium to induce ips cells into salivary gland differentiation, morphological changes of ips cells were observed, CCK-8 was used to determine the cell proliferation efficiency and transcriptome sequencing was used to detect the expression of genes related to parotid gland formation. Results:: Immunofluorescence staining showed that the isolated ips cells were positive for NANOG, SSEA4 and OCT4 and had embryonic-like stem cell characteristics; CCK-8 showed that there was no statistical difference in the proliferation efficiency between the IRF6+induced group and the simple induced group after induction of ips cells into salivary glands. The results of transcriptome sequencing showed that there were a total of 643 differentially expressed genes, including 365 up-regulated genes and 278 down-regulated genes in the IRF6+induced group compared to the blank control group, and the salivary gland related genes HAPLN1, CCL2, MSX2, ANXA1, CYP11A1, HES1 and LUM were all highly expressed in the IRF6+induced group. Conclusion:: IRF6 promotes salivary gland differentiation in urine-derived iPSCs, and its mechanism of promoting differentiation may be that IRF6 upregulates the expression of HAPLN1, CCL2, MSX2, ANXA1, CYP11A1, HES1 and LUM to promote epithelial differentiation.

Background: Intrapapillary capillary loop (IPCL) is an important factor for predicting invasion depth of esophageal squamous cell carcinoma (ESCC). The invasion depth is closely related to the selection of treatment strategy. However, diagnosis of IPCLs is complicated and subject to interobserver variability. This study aimed to develop an artificial intelligence (AI) system to predict IPCLs subtypes of precancerous lesions and superficial ESCC. Methods: Images of magnifying endoscopy with narrow band imaging from three hospitals were collected retrospectively. IPCLs subtypes were annotated on images by expert endoscopists according to Japanese Endoscopic Society classification. The performance of the AI system was evaluated using internal and external validation datasets (IVD and EVD) and compared with that of the 11 endoscopists. Results: A total of 7094 images from 685 patients were used to train and validate the AI system. The combined accuracy of the AI system for diagnosing IPCLs subtypes in IVD and EVD was 91.3% and 89.8%, respectively. The AI system achieved better performance than endoscopists in predicting IPCLs subtypes and invasion depth. The ability of junior endoscopists to diagnose IPCLs subtypes (combined accuracy: 84.7% vs 78.2%, P< 0.0001) and invasion depth (combined accuracy: 74.4% vs 67.9%, P< 0.0001) were significantly improved with AI system assistance. Although there was no significant differences, the performance of senior endoscopists was slightly elevated. Conclusions: The proposed AI system could improve the diagnostic ability of endoscopists to predict IPCLs classification of precancerous lesions and superficial ESCC.

The high incidence of lymphatic metastasis is closely related to poor prognosis and mortality in cancers. Potent inhibitors to prevent pathological lymphangiogenesis and lymphatic spread are urgently needed. The VEGF-C-VEGFR3 pathway plays a vital role in driving lymphangiogenesis and lymph node metastasis. In addition, COX2 in tumor cells and tumor-associated macrophages (TAMs) facilitates lymphangiogenesis. We recently reported that aiphanol, a natural stilbenolignan, attenuates tumor angiogenesis by repressing VEGFR2 and COX2. In this study, we evaluated the antilymphangiogenic and antimetastatic potency of aiphanol using in vitro, ex vivo and in vivo systems. We first demonstrated that aiphanol directly bound to VEGFR3 and blocked its kinase activity with an half-maximal inhibitory concentration (IC50) value of 0.29 μM in an in vitro ADP-GloTMkinase assay. Furthermore, we showed that aiphanol (7.5−30 μM) dose-dependently counteracted VEGF-C-induced proliferation, migration and tubular formation of lymphatic endothelial cells (LECs), which was further verified in vivo. VEGFR3 knockdown markedly mitigated the inhibitory potency of aiphanol on lymphangiogenesis. In 4T1-luc breast tumor-bearing mice, oral administration of aiphanol (5 and 30 mg· kg−1·d−1) dose-dependently decreased lymphatic metastasis and prolonged survival time, which was associated with impaired lymphangiogenesis, angiogenesis and, interestingly, macrophage infiltration. In addition, we found that aiphanol decreased the COX2-dependent secretion of PGE2 and VEGF-C from tumor cells and macrophages. These results demonstrate that aiphanol is an appealing agent for preventing lymphangiogenesis and lymphatic dissemination by synergistically targeting VEGFR3 and inhibiting the COX2-PGE2-VEGF-C signaling axis.

ObjectiveCirculating tumour DNA (ctDNA) sequencing is increasingly used in the clinical management of patients with colorectal cancer. However, the genomic heterogeneity in ctDNA during treatments and its impact on clinical outcomes remain largely unknown.DesignWe conducted a prospective cohort study (NCT04228614) of 171 patients with unresectable metastatic colorectal cancer (mCRC) who underwent first-line treatment and prospectively collected blood samples with or without tumour samples from patients at baseline and sequentially until disease progression or last follow-up.ResultsThe RAS/BRAF alterations in paired baseline tissue and plasma samples from 63 patients displayed a favourable concordance (81.0%, 51/63). After a period of first-line treatment (median time between baseline and last liquid biopsy, 4.67 months), 42.6% (26/61) of RAS-mutant patients showed RAS clearance and 50.0% (5/10) of BRAF-mutant patients showed BRAF clearance, while 3.6% (3/84) and 0.7% (1/135) of patients showed new RAS or BRAF mutations in ctDNA. Patients with plasma RAS/BRAF clearance showed similar progression-free survival (PFS) and overall survival (OS) with patients who remained RAS/BRAF wild-type, while much better outcomes than those who remained RAS/BRAF mutant. Patients who gained new RAS/BRAF mutations showed similar prognosis as those who maintained RAS/BRAF mutations, and shorter PFS and OS than those who remained RAS/BRAF wild-type.ConclusionThis prospective, serial and large-scale ctDNA profiling study reveals the temporal heterogeneity of mCRC-related somatic variants, which should be given special attention in clinical practice, as evidenced by the finding that the shift in plasma RAS/BRAF mutational status can yield a drastic change in survival outcomes.

Byline: Liming. Jiang, Haimiao. Xu, Jun. Lin, Lirong. Tang, Tiemin. Xie, Xing. Yan, Hao. Jiang Objective: The aim was to evaluate the effectiveness of computed tomography (CT)-guided fine-needle aspiration biopsy [...]

Management of forest plantations is a natural based solution to the global‐scale mitigation of climate change; however, the role of carbon sequestration remains poorly understood, and this is hampered by a lack of detailed distribution on the global forest plantations. For the first time, we generated a global spatial distribution for forest plantations (GSDFP) during 2015 at a spatial resolution of 250 m using hierarchical extraction based on a machine learning algorithm taking time series of MODIS and ALOS PALSAR imagery as the source data, and finally estimates the biomass carbon stored in forest plantations. The resultant map was validated using reference samples visually interpreted, as well as reference samples collected from previous studies, and inter‐compared with statistical forest plantation area and regional forest plantation maps, and the GSDFP was found to accurately represent the spatial distribution of forest plantations around the globe. Globally, forest plantations account for 7.35% (360.22 × 104km2) of the global forest area and are estimated to contribute 4.60% (12.85 Pg C) of global forest biomass carbon. The forest plantation map and biomass carbon stock estimates will assist forest management and provide a benchmark for the estimation of the forest plantation carbon sink. In recent decades, global reforestation and afforestation practices have aroused wide concern in the effectiveness of climate change mitigation. However, the lack of spatial explicit data on forest plantations is the vital limitation with respect to the corresponding biomass carbon stock estimates. In this study, we generated the global spatial distribution of forest plantations at a spatial resolution of 250 m, and further estimated the biomass carbon stock in forest plantations. We found that forest plantations contributed less biomass carbon stock to forests than their corresponding area. Our results can provide crucial scientific information for decisions on forest management and climate change mitigation. A global distribution of forest plantations was created using machine learning, and the biomass carbon stock in forest plantations was estimatedThe proportion of plantation area in the forest (360.22 × 104 km2, 7.35%) is higher than that of biomass carbon stocks (12.85 Pg C, 4.60%)The forest plantations map and biomass carbon stock estimates will be beneficial for natural based solutions for climate mitigation A global distribution of forest plantations was created using machine learning, and the biomass carbon stock in forest plantations was estimated The proportion of plantation area in the forest (360.22 × 104 km2, 7.35%) is higher than that of biomass carbon stocks (12.85 Pg C, 4.60%) The forest plantations map and biomass carbon stock estimates will be beneficial for natural based solutions for climate mitigation

In this paper, a novel decentralised robust state feedback sliding mode control is presented to stabilise a class of nonlinear interconnected systems with matched uncertainty and unknown interconnections. A composite sliding surface is designed, and a set of conditions are developed to guarantee that the corresponding sliding motion is uniformly asymptotically stable. Then, a decentralised state feedback sliding mode control is proposed to drive interconnected systems to the designed sliding surface in finite time, and sliding motion occurs thereafter. The bounds on the uncertainties and interconnections are known nonlinear functions, which are employed in the control design to reject the effects of uncertainties and unknown interconnections to enhance the robustness. Finally, a numerical simulation example is given to demonstrate the effectiveness of the proposed control strategy.

Low molecular weight glutenin subunits (LMW-GS), as important seed storage proteins, together with HMW-GS significantly define unique dough viscoelastic properties. In this study, a rapid ultraperformance liquid chromatography (UPLC) method for the separation and characterization of LMW-GS in wheat was optimized and established. The fast, reproducible, and high-resolution UPLC separation of LMW-GS could be obtained by gradually increasing eluting gradient from 21 to 47% in 30 min at flow rate of 0.55 mL/min and 60 °C for separation temperature. By this method, analysis of one sample could be completed in <20 min, significantly less time than the traditional reversed-phase high-performance liquid chromatography (RP-HPLC) method. Under the optimized conditions, the genetic features of LMW-GS and genotype × environmental interaction were successfully analyzed, leading to a fast identification of 17 main LMW-GS alleles that were related to different quality properties in wheat. The results demonstrated that UPLC could be a powerful and alternative tool for genetic and proteomic studies of wheat grain proteins and fast identification or screening of desirable LMW-GS alleles in wheat quality improvement.

As a typical battery-type material, Co–Ni oxide (CoNiO) which was synthesized by a simple co-precipitation method and capacitor-type activated polyaniline-derived carbon (APDC) were used to assemble LIHCs as the anode and cathode electrode materials, respectively. The assembled LIHC exhibits excellent cycle stability with the capacitance retention of ∼78.2% after 15,000 cycles at a current density of 0.5Ag−1.

Cobalt phosphide has received much attention as an efficient catalyst for electrocatalytic hydrodechlorination (EHDC). However, the active species proton hydrogen (H*) is consumed by the hydrogen evolution reaction (HER). Herein, we report a crystal regulation strategy for cobalt phosphate/graphitic nanocarbon/nickel foam (CoPO/GC/NF) catalysts applied for the EHDC of 2,4-dichlorophenoxyacetic acid (2,4-D). Characterization revealed that during the high-temperature phosphatization process, CoPO/GC/NF catalysts developed Co(PO3)2@CoP heterojunctions, enhancing charge transfer at the electrolyte-catalyst interface and water dissociation. The interaction between Co(PO3)2and CoP induced the reconstitution of CoP into the Co–OH species, which facilitated the production of H* by accelerating the Volmer step, enhancing EHDC activity. Furthermore, Co(PO3)2species improve the catalyst tolerance, with CoPO/GC/NF(450) maintaining over 71% yield of phenoxyacetic acid (PA) in continuous testing for up to 80 h under high-salt conditions. This work clarifies the surface transformation process of CoP/GC/NF during hydrodechlorination and demonstrates great potential for chlorophenol wastewater remediation.

Microglia (MG) activation and its mediated neuroinflammation are closely related to the occurrence and deterioration of Alzheimer's disease (AD). Acupuncture is one of the effective approach for AD, which can relieve the symptoms and slow the deterioration of AD. Based on the role of MG activation and its induced pro-inflammatory and anti-inflammatory phenotypes in neuroinflammation, this paper reviews the related literature on the mechanism of acupuncture in regulating MG activation and relieving neuroinflammation in AD. It is found that acupuncture can inhibit abnormal MG activation by regulating the release of MG surface immune receptors and pro-inflammatory/ anti-inflammatory cytokines. It can also modulate the activity of signaling pathways associated with MG polarization, downregulate the expression of M1, and promote MG polarization towards the M2 phenotype. Additionally, it adjusts the imbalance between M1 and M2 phenotypes of MG, thereby relieving the neuroinflammatory pathological procession of and repairing the neuronal damage so as to achieve its therapeutic effect.

Micro-gyroscopes using micro-electro-mechanical system (MEMS) and micro-opto-electro-mechanical system (MOEMS) are the new-generation and recently well-developed gyroscopes produced by the combinations of the traditional gyroscope technology and MEMS/MOEMS technologies. According to the working principle and used materials, the newly-reported micro-gyroscopes in recent years include the silicon-based micromechanical vibratory gyroscope, hemispherical resonant gyroscope, piezoelectric vibratory gyroscope, suspended rotor gyroscope, microfluidic gyroscope, optical gyroscope, and atomic gyroscope. According to different sensitive structures, the silicon-based micromechanical vibratory gyroscope can also be divided into double frame type, tuning fork type, vibrating ring type, and nested ring type. For those micro-gyroscopes, in recent years, many emerging techniques are proposed and developed to enhance different aspects of performances, such as the sensitivity, angle random walk (ARW), bias instability (BI), and bandwidth. Therefore, this paper will firstly review the main performances and applications of those newly-developed MEMS/MOEMS gyroscopes, then comprehensively summarize and analyze the latest research progress of the micro-gyroscopes mentioned above, and finally discuss the future development trends of MEMS/MOEMS gyroscopes.

The publishers of International Journal of Numerical Methods for Heat & Fluid Flow have agreed at the request of the authors to retract the article Mao, J.-J., Tian, S.-F., Yan, X.-J. and Zhang, T.-T. (2019), “Lump solutions and interaction phenomena of the (3+1)-dimensional nonlinear evolution equations”, International Journal of Numerical Methods for Heat & Fluid Flow, Vol. 29 No. 9, pp. 3417-3436. https://doi.org/10.1108/HFF-02-2019-0160 Upon thorough review of this paper, the authors have come to the realisation that the content does not meet the level of richness they expected. The authors believe it is necessary to further strengthen and refine the content, therefore, this article has been retracted at the request of the authors and in agreement with the publisher. The publishers of the journal sincerely apologize to the readers. The retracted article is available at: https://doi.org/10.1108/HFF-02-2019-0160

Purpose: Microblog has become an important tool of social marketing since 2010. Compared with traditional blog, microblog has several distinctive features, such as ease of use, viral transmission, high interactivity and real-time communication. Microblog provides a communication platform for companies and consumers; however, it challenges companies’ consumer-brand relationship management. The purpose of this paper is to investigate the influencing mechanism of microblog interaction tactics on consumer-brand relationship. Design/methodology/approach: Based on grounded theory, 66 representative companies’ posts on Weibo are collected, with 1,395 company posts and 5,959 following posts. An influence mechanism model of company microblog interaction tactics on consumer-brand relationship is proposed, then the saturation level of this mechanism is tested. Findings: Results show that: first, companies adopt two types of tactics in microblog interaction: social interaction and task-oriented interaction; second, microblog interaction arises consumers’ emotional response and cognition toward specific brand and eventually influences consumer-brand relationship. Consumers’ emotional response includes pleasure and arousal, brand cognition includes perceived quality, perceived relatedness with companies and brand resonance; third, the influence mechanism differs among different consumer knowledge level, industry and brand awareness. Practical implications: This study provides insight into the use of microblog interaction tactics. Companies may cross-use social interaction and task-oriented interaction tactics to enhance consumer-brand relationship. Companies need to produce microblog content based on the interests of consumers and further establish and improve fan feedback mechanism. Originality/value: This paper constructs a model of the influence of company microblog interaction tactics on consumers. This study finds that co-creation activities initiated by companies are the new tactics to attract consumers on microblog. The finding adds new knowledge to the literature of company consumer interaction and provides a theoretical basis for the practice of microblog marketing.

Amblyopia greatly affects the physical and mental development of children. Acupuncture is effective for amblyopia, though its mechanism remains unclear. This article summarized the mechanism of acupuncture treatment of amblyopia from the perspectives of morphology of neurons in visual cortex, visual electrophysiology, and molecular biology, etc. It was found that acupuncture may treat amblyopia through repairing the morphological and ultrastructural damages of neurons in visual cortex, promoting the electrical activities in visual pathway and visual cortical neurons, and modulating the synthesis and expression levels of factors involved in visual system. Nevertheless, further studies are required to unveil the mechanism of acupuncture treatment of amblyopia. 弱视严重影响患儿生理及心理发育。 针刺疗法是治疗弱视的有效方法之一, 但对其机制尚未完全明确。 从视皮层神经元形态学、 视觉电生理、 分子生物学等方面总结针刺干预弱视的机制, 发现针刺通过修复视皮层神经元形态及超微结构损害, 促进视觉通路及视皮层神经元电活动, 调控视觉系统相关分子合成和表达水平达到 干预弱视的目的。 对于针刺干预弱视机制仍需进一步研究。

The rockfill exhibits a substantial amount of particle breakage when subjected to higher range of stresses. The deformations of rockfill under such excessive stresses often lead to failure and cannot be ignored. The degree of particle breakage is related to the type of the material as well as the particle shape. Based on this, artificially simulated rockfill materials with three different aggregate shapes (prism, cube, and cylinder) were prepared by cement paste-casting method. Through a series of medium-sized triaxial shear tests, the effects of confining pressure and particle shape on the fracture characteristics of the artificial rockfill and its secant modulus were investigated. The useful relationships between particle sphericity and roundness with deformation modulus and particle breakage rate were proposed.

To observe the effects of acupuncture on the characteristics of neuro-electrophysiological activity in hippocampal CA1 and CA3 areas of rats with post-traumatic stress disorder (PTSD). Fifty Sprague-Dawley (SD) rats were randomly divided into a blank group, a model group, a grasping group, a Western medicine group and an acupuncture group, with 10 rats in each group. Except for the blank group, rats in the other 4 groups all received the combined stress modeling method. Rats in the Western medicine group were intragastrically administrated with paroxetine hydrochloride, those in the acupuncture group received acupuncture intervention, those in the grasping group received grasping fixation, and those in the model group and the blank group did not receive any interventions. After 14 d of intervention, the interspike interval (ISI) and power spectral densities (PSD) were analyzed and mapped by in vivomultiple channels to record the neuron clusters discharge in the hippocampal CA1 and CA3 areas. Compared with the blank group, ISI was prolonged in the CA1 and CA3 areas of the model group and the grasping group, and the concentrated PSD distribution area moved down (P<0.05 or P<0.01). Compared with the grasping group, the ISI of the CA1 and CA3 areas in the Western medicine group and the acupuncture group was shortened, and the concentrated PSD distribution area moved up (P<0.05 or P<0.01). The ISI and PSD distributions in the CA1 and CA3 areas of the acupuncture group were not statistically different from those in the Western medicine group (both P>0.05). Both acupuncture and paroxetine hydrochloride can significantly regulate the neuro-electrophysiology activity of hippocampal CA1 and CA3 areas in PTSD rats, which may be one of the mechanisms of acupuncture intervention to promote PTSD recovery. 观察毫针针刺对创伤后应激障碍(PTSD)模型大鼠海马 CA1 和 CA3 区神经电生理活动特征量的影响。 将 50 只 Sprague-Dawley (SD) 大鼠随机分为空白组、 模型组、 抓取组、 西药组和针刺组, 每组 10 只。 除空 白组外, 其他 4 组大鼠以复合应激法造模。 造模同时西药组予以盐酸帕罗西汀灌胃, 针刺组接受针刺干预, 抓取组接受抓取固定, 模型组和空白组不接受任何干预。 干预 14 d 后, 通过在体多通道记录海马 CA1 和 CA3 区神经元集群放电, 分析峰-峰间期(ISI)和功率谱密度(PSD)并绘图。 与空白组比较, 模型组和抓取组 CA1 和 CA3 区 ISI 延长, PSD 集中分布区域下移(P<0.05 或P<0.01); 与抓取组比较, 西药组和针刺组 CA1 和 CA3 区 ISI 缩短, PSD 集中分布区域上移(P<0.05 或P<0.01); 针刺组 CA1 和 CA3 区的 ISI 和 PSD 集中分布区域与西药组无统计学差异(均 P>0.05)。 毫针针刺与盐酸帕罗西汀干预均可显著调节 PTSD 模型大鼠海马 CA1 和 CA3 区神经电生理活动特征量发放模式, 可能是针灸干预促进PTSD 恢复的机制之一。

To observe the effect of acupuncture on blood oxygen concentration in the brain of rats with post-traumatic stress disorder (PTSD) based on functional near-infrared spectroscopy (fNIRS), thus to reveal the mechanisms of acupuncture in intervening the brain function of PTSD rats. Sixty Sprague-Dawley (SD) rats were randomly divided into a blank group, a model group, a grasping group, a paroxetine group and an acupuncture group, with 12 rats in each group. Except the blank group, rats in the other groups all received incarceration plus electric shock for 7 d to prepare the PTSD animal model. One hour before the stress model was established, rats in each group received the designated intervention: rats in the blank group and the model group did not receive any intervention; rats in the grasping group received grasping and fixation; rats in the paroxetine group received paroxetine hydrochloride solution by intragastric administration; and rats in the acupuncture group received acupuncture. Six-day treatment was a course, with 2 courses of treatment conducted for a total of 12 d. After the modeling, rats in each treatment group received intervention for 5 d, and the fNIRS system was used to collect and record the changes in the concentrations of oxygenated hemoglobin (HbO2), deoxygenated hemoglobin (d-Hb) and total hemoglobin (t-Hb) of the involved rat’s brain regions, and also to assess the brain function. Compared with the blank group, the concentration of HbO2 was significantly increased, the concentration of d-Hb was significantly decreased, and the concentration of t-Hb was significantly increased in the model group and the grasping group after the intervention, and the differences were statistically significant (all P<0.01). Compared with the model group, the concentrations of HbO2, d-Hb and t-Hb in the grasping group did not change significantly (all P>0.05). Compared with the grasping group, the concentration of HbO2was significantly decreased, the concentration of d-Hb was significantly increased, and the concentration of t-Hb was significantly decreased in the paroxetine group and the acupuncture group, and the differences were statistically significant (all P<0.05). There were no significant differences in the concentrations of HbO2, d-Hb and t-Hb between the paroxetine group and the acupuncture group (all P>0.05). Acupuncture can regulate the blood oxygen concentration in the brain of PTSD model rats, which may be an important mechanism of acupuncture in intervening the brain function in PTSD rats. 基于功能近红外光谱技术(fNIRS)观察针刺对创伤后应激障碍(PTSD)模型大鼠脑部血氧浓度的影响, 揭示针刺干预PTSD的脑功能机制。 将60只Sprague-Dawley (SD)大鼠随机分为空白组、模型组、抓取组、帕 罗西汀组和针刺组, 每组12只。除空白组外, 其余各组大鼠均以电击幽闭法复制PTSD动物模型, 模型复制共7 d。 于应激造模前1 h, 各组接受相应干预: 空白组和模型组不接受任何干预, 抓取组接受抓取固定, 帕罗西汀组接受 盐酸帕罗西汀溶液灌胃, 针刺组接受针刺治疗, 6 d为1个疗程, 连续干预2个疗程, 共计12 d。造模结束后, 各治疗 组连续治疗5 d后利用fNIRS系统采集并记录各组大鼠相关脑区组织氧合血红蛋白(HbO2)、脱氧血红蛋白(d-Hb) 和 总血红蛋白(t-Hb)浓度的变化情况, 并进行脑功能评估。 干预结束后, 与空白组比较, 模型组和抓取组大鼠 HbO2浓度显著升高, d-Hb浓度显著降低, t-Hb浓度显著升高,差异均具有统计学意义(均P<0.01); 与模型组比较, 抓取组大鼠HbO2、d-Hb和t-Hb浓度均无明显变化(均P>0.05); 与抓取组比较, 帕罗西汀组和针刺组大鼠HbO2浓度 显著降低, d-Hb浓度显著升高, t-Hb浓度显著降低, 差异均具有统计学意义(均P<0.05); 帕罗西汀组与针刺组的 HbO2、d-Hb和t-Hb浓度均无统计学差异(均P>0.05)。 针刺对PTSD模型大鼠脑区血氧浓度有良性的调节作用, 这可能是针刺干预PTSD的重要脑功能机制。