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Abstract This study investigates the prediction of ground loss rate during soft-soil shield tunneling using Peck’s back analysis method and XGBoost model. Bayesian optimization is employed to determine optimal hyperparameters, ensuring comprehensive and efficient model tuning. The XGBoost model is compared with Random Forest (RF) and Support Vector Machine (SVM) models to benchmark its performance. The results demonstrate the superior accuracy and robustness of the XGBoost model. Also, the results show that the soil properties and the grouting factors of the excavation face affect the duration of the instantaneous settlement of the ground surface. There is a specific correlation between the depth-to-diameter ratio, the coefficient of variation in the advancing speed of the shield machine, the maximum surface subsidence, and the ground loss rate. The prediction model of the ground loss rate based on the combined approach of Peck back analysis and eXtreme Gradient Boosting and Bayesian optimization has high reliability in soft-soil layers, and this method can provide a specific reference for predicting construction risk in related projects.

Background: Long non-coding RNAs (lncRNAs) can be incorporated into exosomes to mediate the intercellular communication, regulating the occurrence, development, and immunosuppression of cancers. T cell dysfunction has been a hallmark of many cancers, including melanoma, which enables cancer cells escape from host immune surveillance. However, the molecular mechanism of exosome-transmitted lncRNAs in CD8+ T cell dysfunction in melanoma remains largely unclear. Method: The expression of circulating LINC01214 (cirLINC01214) was detected by quantitative real-time polymerase chain reaction (RT-qPCR). Exosomes were isolation from the culture medium and plasma of melanoma patients via ultracentrifugation and characterized by transmission electronic microscopy. The regulation of exosomal LINC01214 on CD8+ T cell function was determined by ELISA. The molecular mechanism of exosomal LINC01214 in CD8+ T cells were assessed by the RNA immunoprecipitation and pull-down assay. A mouse model with reconstituted human immune system was used to explore the role of exosomal LINC01214 in the resistance to anti-PD1 therapy. Results: LINC01214 was highly expressed in melanoma tissues compared with matched adjacent normal tissues. Increased levels of circulating LINC01214 (cirLINC01214) was observed in melanoma patient plasma and correlated with poor PD-1 immunotherapy response. The cirLINC01214 was predominantly released by melanoma cells in an exosome manner. Melanoma cell-derived exosomal LINC01214 inhibits the production of IFN-γ, TNF-α, Granzyme-B and Perforin by CD8+ T cells. Further mechanism study found that cirLINC01214 delivered by exosomes suppressed CD8+ T cell function by up-regulating the expression of Protein Phosphatase 1 Regulatory Inhibitor Subunit 11 (PPP1R11) through sponging miR-4492. CirLINC01214 conferred resistance to PD-1 immunotherapy in melanoma xenograft mouse model. Melanoma patients with poor prognosis after PD-1 treatment carried high levels of exosomal LINC01214. Additionally, the secretion of exosomal cirLINC01214 was enhanced by the Warburg effect, which was consistent with the reprogrammed glucose metabolism of melanoma. Conclusions: Our results demonstrated that exosomal LINC01214 released by melanoma cells promoted immunotherapy resistance by inducing CD8+ T cell dysfunction via the miR-4492/PPP1R11 regulatory loop. Targeting cirLINC01214 might be a potential therapeutic strategy to enhance the outcome of immunotherapy in melanoma.

PurposeThis study aimed to compare postoperative gastrointestinal symptoms between patients who underwent laparoscopic distal gastrectomy with Roux-en-Y (R-Y) and Billroth-II with Braun (B-II B) reconstruction.MethodsThis observational study retrospectively analyzed 151 patients (110 in R-Y group and 41 in B-II B group) who underwent laparoscopic distal gastrectomy from January 2020 to December 2021. A comparison was made regarding surgical outcomes, perioperative nutritional and inflammatory markers, postoperative dietary patterns, and gastrointestinal symptoms between the two groups.ResultsThe operation time was longer in the R-Y group than the B-II B group (261.00 ± 56.17 min versus 239.88 ± 57.78 min, p = 0.046). However, there were no significant differences in the length of hospital stay, ASA classification, complications, nutritional and inflammatory indexes, or recovery of postoperative diet between the two groups. Additionally, there were no significant differences in the occurrence of postoperative gastrointestinal symptoms in the post-discharge week (PDW) 1 and postoperative month (POM) 1 between the B-II B and R-Y groups.ConclusionsAbdominal distention emerged as the main gastrointestinal symptom burden in patients with gastric cancer undergoing laparoscopic distal gastrectomy. Both Billroth-II with Braun and R-Y reconstructions exhibited a high and similar incidence of gastrointestinal symptoms in the short term. Therefore, medical staff should pay attention to the management of gastrointestinal symptoms in these patients postoperatively.

Soil-pipeline separation due to tunnelling has been certainly substantiated in previous model tests. However, this phenomenon has seldom been considered in current analytical solutions. This study formulates a tensionless Winkler solution that could make allowance for gap formation in soil-pipeline interaction analyses. The solution is validated by comparisons with existing experimental measurements and two recognized analytical solutions. Also, its advantage over an existing Winkler solution is addressed. Further parametric studies reveal that the effects of gap formation on the response of a pipeline rely largely on the tunnel volume loss and the pipeline’s bending stiffness and burial depth. In general, a pipeline’s bending moments and subgrade reaction forces are more susceptible than its deflections to the gap formation.

Abstract The emergence of microhemispherical resonant gyroscopes, which integrate the advantages of exceptional stability and long lifetime with miniaturization, has afforded new possibilities for the development of whole-angle gyroscopes. However, existing methods used for manufacturing microhemispherical resonant gyroscopes based on MEMS technology face the primary drawback of intricate and costly processing. Here, we report the design, fabrication, and characterization of the first 3D-printable microhemispherical shell resonator for a Coriolis vibrating gyroscope. We remarkably achieve fabrication in just two steps bypassing the dozen or so steps required in traditional micromachining. By utilizing the intricate shaping capability and ultrahigh precision offered by projection microstereolithography, we fabricate 3D high-aspect-ratio resonant structures and controllable capacitive air gaps, both of which are extremely difficult to obtain via MEMS technology. In addition, the resonance frequency of the fabricated resonators can be tuned by electrostatic forces, and the fabricated resonators exhibit a higher quality factor in air than do typical MEMS microhemispherical resonators. This work demonstrates the feasibility of rapidly batch-manufacturing microhemispherical shell resonators, paving the way for the development of microhemispherical resonator gyroscopes for portable inertial navigation. Moreover, this particular design concept could be further applied to increase uptake of resonator tools in the MEMS community.

ABSTRACTA thorough assessment of the karst ecosystem quality plays an important role in regional sustainable development. In this study, based on multi-source remote sensing data, a comprehensive ecosystem quality index (EQI) was developed by integrating the ecosystem function index (EFI), the ecosystem stability index (ESI), and the ecosystem stress index (ESSI), to evaluate the spatio-temporal changes of ecosystem quality in the karst region of Southwest China during the past two decades. The results showed that the EFI exhibited a significant increasing trend in approximately 54.58% of the karst area from 2001 to 2020. The ESI experienced multiple stages from initially increasing around 2005, then decreasing around 2010, and finally increasing to the peak in 2020. The ESSI fluctuated at a high level since 2001. Overall, the comprehensive EQI experienced a gradual improvement in the initial period from 2001 to 2010, and then increased significantly from 2015 to 2020. The excellent EQI occupied by no more than 20% before 2005, but expanded sharply with about three times by 2020. Additionally, nearly 16.73% of the karst area experienced significant improvement in the EQI, whereas only 0.28% of the karst area exhibited severe degradation in the EQI during the past 20 years.

ABSTRACTVegetation phenological metrics have attracted increasing attentions during recent years. However, compared with the peak greenness timing (PGT), the peak photosynthesis timing (PPT) has been overlooked until now. As the world's third pole, the Tibetan Plateau is one of the most sensitive areas to global climatic change. In this study, long-term time-series solar-induced chlorophyll fluorescence (SIF) data were used to identify the PPT patterns, trends, and responses in the Tibetan Plateau over the past two decades. Our findings indicated that the SIF-derived PPT can better capture the characteristics from flux-measured gross primary productivity compared with the MODIS EVI-based PGT, exhibiting great potential to characterize large-scale vegetation PPT dynamics. The multi-year mean PPT mainly appeared in late July and early August with a gradually delayed trend from southeast to northwest. Meanwhile, early PPT occurred in many areas of the Tibetan Plateau (67.36%), with the overall trend advanced by about 0.89 day decade−1. Interestingly, opposite trends of PPT were found with elevation below and above 2500 m asl. Preseason temperature, shortwave radiation, and precipitation jointly explained the strong spatial heterogeneity of PPT trend. All analyses help clarify the role of the ‘third pole’ in responding to environmental change and regional carbon cycles.

Abstract Flexible pressure sensors play a significant role in wearable devices and electronic skin. Iontronic pressure sensors with high sensitivity, wide measurement range, and high resolution can meet requirements. Based on the significant deformation characteristics of alveoli to improve compressibility, and the ability of the arch to disperse vertical pressure into horizontal thrust to increase contact area, a graded hollow ball arch (GHBA) microstructure is proposed, greatly improving sensitivity. The fabrication of GHBA ingeniously employs a double‐sided structure. One side uses mold casting to create convex structures, while the other utilizes the evaporation of moisture during the curing process to form concave structures. At the same time, a novel side‐by‐side package structure is proposed, ensuring pressure on flexible substrate is maximally transferred to the GHBA microstructure. Within the range of 0.2 Pa–300 kPa, the iontronic pressure sensor achieves a maximum sensitivity of 10 420.8 kPa−1, pressure resolution of 0.1% under the pressure of 100 kPa, and rapid response/recovery time of 40/35 ms. In wearable devices, it is capable of monitoring dumbbell curl exercises and wirelessly correcting sitting positions. In electronic skin, it can non‐contactly detect the location of the wind source and achieve object classification prediction when combined with the CNN model.

Human body motion segmentation plays a major role in many applications, ranging from computer vision to robotics. Among a variety of algorithms, graph-based approaches have demonstrated exciting potential in motion analysis owing to their power to capture the underlying correlations among joints. However, most existing works focus on simpler single-layer geometric structures, whereas multi-layer spatial-temporal graph structure can provide more informative results. To provide an interpretable analysis on multilayer spatial-temporal structures, we revisit the emerging field of multilayer graph signal processing (M-GSP), and propose novel approaches based on M-GSP to human motion segmentation. Specifically, we model the spatial-temporal relationships via multilayer graphs (MLG) and introduce M-GSP spectrum analysis for feature extraction. We present two different M-GSP based algorithms for unsupervised segmentation in the MLG spectrum and vertex domains, respectively. Our experimental results demonstrate the robustness and effectiveness of our proposed methods.

In this paper, a novel signal processing method combining mathematical morphology (MM) and Walsh theory is proposed, which uses Walsh functions to control the structuring element (SE) and MM operators. Based on the Walsh-MM method, a scheme for power quality disturbances detection and classification is developed, which involves three steps: denoising, feature extraction and morphological clustering. First, various evolution rules of Walsh function are used to generate groups of SEs for the multiscale Walsh-ordered morphological operation, so the original signal can be denoised. Next, the fundamental wave of the denoised signal is suppressed by Hadamard matrix; thus, disturbances can be extracted. Finally, the Walsh power spectrum of the waveform extracted in the previous step is calculated, and the parameters of which are taken by morphological clustering to classify the disturbances. Simulation results reveal the proposed scheme can effectively detect and classify disturbances, and the Walsh-MM method is less affected by noise and only involves simple calculation, which has a potential to be implemented in hardware and more suitable for real-time application.

By leveraging spatial diversity, MultiUser MIMO (MU-MIMO) can serve multiple users over shared time-frequency Resource Blocks (RBs) and substantially improve spectral efficiency. However, performances of wideband MU-MIMO systems are severely limited by both frequency-selective channels and Co-Channel Interference (CCI) among users. To reach the full potential of MU-MIMO, users should be scheduled at RBs with decent channel gains and minimal CCIs. Since such scheduling problem is NP-hard and the transmission time interval of modern wireless systems is ultra-short, it is critical to design efficient algorithms that can make satisfactory sub-optimal user scheduling decisions in real-time. Nonetheless, existing works either rely on heuristics or may not readily be applied to wideband system. To tackle these challenges, we propose a novel Unsupervised Learning-Aided Wideband Scheduling (ULAWS) framework. Specifically, ULAWS first utilizes Multi-Dimensional Scaling (MDS) based graph embedding and clustering to obtain intrinsic user groups with low CCI among co-channel users. Based on clustering results, we adopt Gale-Sharpley algorithm to find a stable matching between users and RBs. Next, a graph-based post-processing procedure stacked with three efficient steps is applied as refinement. Simulation results demonstrate performance gain over benchmark methods in terms of sum rate, fairness and outage rate, under various system parameters and scenarios.

Land surface temperature (LST), especially day-night LST difference $\lpar {{\rm LS}{\rm T}_{\rm d}-{\rm LS}{\rm T}_{\rm n}} \rpar$, is a key variable for the stability of terrestrial ecosystems, affected by vegetation and climate change. Quantifying the contribution and feedback of vegetation and climate to LST changes is critical to developing mitigation strategies. Based on LST, Normalized vegetation index (NDVI), land use (LU), air temperature (AT) and precipitation (Pre) from 2003 to 2021, partial correlation was used to analyze the response of LST to vegetation and climate. The feedback and contribution of both to LST were further quantified by using spatial linear relationships and partial derivatives analysis. The results showed that both interannual LST $\lpar {{\rm LS}{\rm T}_{\rm y}} \rpar$ and ${\rm LS}{\rm T}_{\rm d}-{\rm LS}{\rm T}_{\rm n}$ responded negatively to vegetation, and vegetation had a negative feedback effect in areas with significantly altered. Vegetation was also a major contributor to the decline of ${\rm LS}{\rm T}_{\rm d}-{\rm LS}{\rm T}_{\rm n}.$ With the advantage of positive partial correlation area of 94.99%, AT became the main driving factor and contributor to ${\rm LS}{\rm T}_{\rm y}$ change trend. Pre contributed negatively to both ${\rm LS}{\rm T}_{\rm y}$ and ${\rm LS}{\rm T}_{\rm d}-{\rm LS}{\rm T}_{\rm n}$, with contributions of −0.004 °C/y and −0.022 °C/y, respectively. AT played a decisive role in LST warming of YRB, which was partially mitigated by vegetation and Pre. The present research contributed to the detection of LST changes and improved understanding of the driving mechanism.

In recent years, past changes in global and regional land surface temperatures (LST) have been well studied, however, future LST changes have been largely ignored owing to data limitations. In this study, three climate variables of CMIP6, namely air temperature (AT), precipitation (Pre), and leaf area index (LAI), were spatially corrected using the Delta downscaling method. On this basis, by combining MODIS LST, elevation, slope and aspect, a random forest (RF) model was built to calculate the LST from 2022 to 2100. The absolute variability (AV) and Mann-Kendall (M-K) tests were used to quantitatively detect interannual and seasonal LST changes in different Shared Socioeconomic Pathways (SSPs) scenarios. The results showed that the AV value increased successively from SSP1-2.6 to SSP2-4.5 and then to SSP5-8.5. Compared with the base period (2003-2021), the increment in interannual, spring, summer and autumn LST during 2022–2100 was mainly between 1 and 2 °C under three scenarios. The interannual and seasonal LST were spatially characterized by significant warming over large areas, and the increasing was the fastest under SSP5-8.5. These results indicate that, in the future, LST will increase further over large areas, especially in winter.

The accurate modeling of single-particle breakage based on three-dimensional (3D) images is crucial for understanding the particle-level mechanics of granular materials. This study aims to propose a systematic framework incorporating single-particle breakage experiments and numerical simulations based on a novel 3D particle reconstruction technique for fractal analysis of particle size and morphology in single-particle breakage. First, the vision foundation model is used to generate accurate particles from 3D images. The numerical approach is validated by simulating the single-particle breakage test with multiple Fujian sand particles. Then, the breakage processes of reconstructed sand particles under axial compression are numerically modeled. The relationship between 3D fractal dimensions and particle size, particle crushing strength, and morphology is meticulously investigated. Furthermore, the implications of these relationships on the particle breakage processes are thoroughly discussed, shedding light on the underlying mechanisms that govern particle breakage. The framework offers an effective way to investigate the breakage behavior of single sand particles, which will enhance understanding of the mechanism of the whole particle breakage process.

Abstract Cytoplasmic male sterility (CMS) lines are important for breeding hybrid crops, and utilization of CMS lines requires strong fertility restorer (Rf) genes. Rf4, a major Rf for Wild-Abortive CMS (CMS-WA), has been cloned in rice. However, the Rf4 evolution and formation of CMS-WA/Rf system remain elusive. Here, we show that the Rf4 locus emerges earlier than the CMS-WA gene WA352 in wild rice, and 69 haplotypes of the Rf4 locus are generated in the Oryza genus through the copy number and sequence variations. Eight of these haplotypes of the Rf4 locus are enriched in modern rice cultivars during natural and human selections, whereas non-functional rf4i is preferentially selected for breeding current CMS-WA lines. We further verify that varieties carrying two-copy Rf4 haplotype have stronger fertility restoration ability and are widely used in three-line hybrid rice breeding. Our findings increase our understanding of CMS/Rf systems and will likely benefit crop breeding.

Crack detection is significant to building repair and maintenance; however, conventional inspection is a labor-intensive and time-consuming process for field engineers. This paper proposes a three-step computer vision-based framework to quickly recognize concrete cracks and automatically identify their length, maximum width, and area in damage images. In step one, a region-based convolutional neural network (YOLOv8) is applied to train the crack localizing model. In step two, Gaussian filtering, Canny, and FindContours are integrated to extract the reference contour (a pre-designed seal) to obtain the conversion scale between pixels and millimeter-wise sizes. In step three, the recognized crack bounding box is cropped, and the ApproxPolyDP function and Hough transform are performed to quantify crack dimensions based on the conversion ratio. The developed framework was validated on a dataset of 4630 crack images, and the model training took 150 epochs. Results show that the average crack detection accuracy reaches 95.7%, and the precision of quantified dimensions is over 90%, while the error increases as the crack size grows smaller (increasing to 8% when the crack width is within 1 mm). The proposed method can help engineers to efficiently achieve crack information at building inspection sites, while the reference frame must be pre-marked near the crack, which may limit the scope of application scenarios. In addition, the robustness and accuracy of the developed image processing techniques-based crack quantification algorithm need to be further improved to meet the requirements in real cases when the crack is located within a complex background.

Abstract Melanoma is considered as the most common metastatic skin cancer with increasing incidence and high mortality globally. The vital roles of long non-coding RNAs (lncRNAs) in the tumorigenesis of melanoma are elucidated by emerging evidence. The lncRNA cervical carcinoma high-expressed 1 (CCHE1) was overexpressed and acted as an oncogene in a variety of cancers, while the function of CCHE1 in melanoma remains unclear. Here, we found that CCHE1 was highly expressed in melanoma and correlated with the poorer survival of melanoma patients. Depletion of CCHE1 inhibited the proliferation, induced cell apoptosis and suppressed in vivo tumor growth. To further understand the functional mechanism of CCHE1, the interacting partners of CCHE1 were identified via RNA pull-down assay followed by mass spectrometry. CCHE1 was found to bind lactate dehydrogenase A (LDHA) and acted as a scaffold to enhance the interaction of LDHA with the fibroblast growth factor receptor type 1 (FGFR1), which consequently enhanced LDHA phosphorylation and activity of LDHA. Inhibiting CCHE1 strikingly suppressed the glycolytic flux of melanoma cells and lactate generation in vivo. Further study demonstrated that CCHE1 desensitized melanoma cells to dacarbazine and inhibition of glycolysis reversed CCHE1-induced chemoresistance. These results uncovered the novel function of CCHE1 in melanoma by reprogramming the glucose metabolism via orchestrating the activity of LDHA.

As a geological barrier for high-level radioactive waste (HLW) disposal in China, granite is crucial for blocking nuclide migration into the biosphere. However, the high uncertainty associated with the 3D geological system, such as the stochastic discrete fracture networks in granite, significantly impedes practical safety assessments of HLW disposal. This study proposes a Monte Carlo simulation (MCS)-based simulation framework for evaluating the long-term barrier performance of nuclide migration in fractured rocks. Statistical data on fracture geometric parameters, on-site hydrogeological conditions, and relevant migration parameters are obtained from a research site in Northwestern China. The simulation models consider the migration of three key nuclides, Cs-135, Se-79, and Zr-93, in fractured granite, with mechanisms including adsorption, advection, diffusion, dispersion, and decay considered as factors. Subsequently, sixty MCS realizations are performed to conduct a sensitivity analysis using the open-source software OpenGeoSys-5 (OGS-5). The results reveal the maximum and minimum values of the nuclide breakthrough time Tt (12,000 and 3600 years, respectively) and the maximum and minimum values of the nuclide breakthrough concentration Cmax (4.26 × 10−4 mSv/a and 2.64 × 10−5 mSv/a, respectively). These significant differences underscore the significant effect of the uncertainty in the discrete fracture network model on long-term barrier performance. After the failure of the waste tank (1000 years), nuclides are estimated to reach the outlet boundary 6480 years later. The individual effective dose in the biosphere initially increases and then decreases, reaching a peak value of Cmax = 4.26 × 10−4 mSv/a around 350,000 years, which is below the critical dose of 0.01 mSv/a. These sensitivity analysis results concerning nuclide migration in discrete fractured granite can enhance the simulation and prediction accuracy for risk evaluation of HLW disposal.

Soil arching is significantly influenced by relative density, while its mechanisms have barely been analyzed. A series of DEM numerical simulations of the classical trapdoor test were carried out to investigate the multi-scale mechanisms of arching development and degradation in granular materials with different relative density. For analysis, the granular assembly was divided into three zones according to the particle vertical displacement normalized by the trapdoor displacement δ. The results show that before the maximum arching state (corresponding to the minimum arching ratio), contact forces between particles in a specific zone (where the vertical displacement of particles is larger than 0.1δ but less than 0.9δ) increase rapidly and robust arched force chains with large particle contact forces are generated. The variation in contact forces and force chains becomes more obvious as the sample porosity decreases. As a result, soil arching generated in a denser particle assembly is stronger, and the minimum value of the arching ratio is increased with the sample porosity. After the maximum arching state, the force chains in this zone are degenerated gradually, leading to a decrease in particle contact forces in microscale and an increase in the arching ratio in macroscale. The recovery of the arching ratio after the minimum value is also more significant in simulations with a larger relative density, as the degeneration of contact force chains is more obvious in denser samples. These results indicate the importance of contact force chain stabilities in specific zones for improving soil arching in engineering practice.

Climate change inevitably affects vegetation growth in the Tibetan Plateau (TP). Understanding the dynamics of vegetation phenology and the responses of vegetation phenology to climate change are crucial for evaluating the impacts of climate change on terrestrial ecosystems. Despite many relevant studies conducted in the past, there still remain research gaps concerning the dominant factors that induce changes in the start date of the vegetation growing season (SOS). In this study, the spatial and temporal variations of the SOS were investigated by using a long-term series of the Normalized Difference Vegetation Index (NDVI) spanning from 2001 to 2020, and the response of the SOS to climate change and the predominant climatic factors (air temperature, LST or precipitation) affecting the SOS were explored. The main findings were as follows: the annual mean SOS concentrated on 100 DOY–170 DOY (day of a year), with a delay from east to west. Although the SOS across the entire region exhibited an advancing trend at a rate of 0.261 days/year, there were notable differences in the advancement trends of SOS among different vegetation types. In contrast to the current advancing SOS, the trend of future SOS changes shows a delayed trend. For the impacts of climate change on the SOS, winter Tmax (maximum temperature) played the dominant role in the temporal shifting of spring phenology across the TP, and its effect on SOS was negative, meaning that an increase in winter Tmax led to an earlier SOS. Considering the different conditions required for the growth of various types of vegetation, the leading factor was different for the four vegetation types. This study contributes to the understanding of the mechanism of SOS variation in the TP.

Water-level fluctuation (WLF) can destroy soil aggregates and induce soil organic carbon (SOC) loss, potentially triggering impacts on the concentration of atmospheric carbon dioxide. However, responses of soil aggregate content and aggregate-associated organic carbon to WLF have not been well studied, especially in the water-level fluctuation zone (WLFZ) of the Three Gorges Reservoir (TGR). Therefore, samples from different elevations (145 m, 155 m and 165 m) in the WLFZ of the TGR were collected for experiments. The wet sieving method was used to divide soil into silt and clay (0.25 mm). The K2Cr2O7-H2SO4 oxidation method was used to measure total SOC content in different soil aggregates. A modified Walkley and Black method was used to measure labile carbon in different soil aggregates. Results showed that macro-aggregate content substantially decreased, while micro-aggregate content remained stable and silt and clay fraction accumulated with a decrease in water-level elevations. Moreover, total SOC content and labile carbon in macro-aggregate were obviously higher than those in the micro-aggregate and the silt and clay fraction. Macro-aggregate contributed the most to SOC sequestration, while micro-aggregate contributed the least, and the contribution of macro-aggregate increased with a decrease in water-level elevations. We concluded that the macro-aggregate was the most active participant in the SOC sequestration process, and preferentially increasing the macro-aggregate content of the lowest water-level elevation was conducive to an improvement in soil carbon sequestration potential and would mitigate climate change.

Real-time monitoring of rainwater is a critical issue in the development of autonomous vehicles and smart homes, while the corresponding sensors play a pivotal role in ensuring their sensitivity. Here, we study a self-powered intelligent water droplet monitoring sensor based on a solid–liquid triboelectric nanogenerator (SL-TENG). The sensor comprises a SL-TENG, a signal acquisition module, a central processing unit (CPU), and a wireless transmission module, facilitating the real-time monitoring of water droplet signals. It is worth noting that the SL-TENG has self-powering characteristics and can convert the kinetic energy of water droplets into electrical energy. The excellent output performance, with open-circuit voltage of 9 V and short-circuit current of 2 μA without any treatment of the SL-TENG, can provide an effective solution to the problem that traditional sensor need battery replacement. In addition, the SL-TENG can generate stable amplitude electrical signals through water droplets, exemplified by the absence of decay in a short-circuit current within 7 days. More importantly, the sensor is equipped with intelligent analytical capabilities, allowing it to assess rainfall based on variables such as amplitude and frequency. Due to its excellent stability and intelligent analysis, this sensor can be used for roof rainwater monitoring, intravenous administration monitoring, and especially in automobile automatic wipers and other fields.

In recent years, language function impairment caused by intracranial diseases has gained increasing interest, mainly due to its significant impact on the language and cognitive ability, leading to a serious decline in the quality of life of patients. Consequently, researchers aimed to clarify the quantitative degree of lesions of the arcuate fasciculus and therapeutic targets to promote nerve fiber remodeling. The arcuate fasciculus is extremely prone to damage caused by diseases such as stroke and brain tumor. Hallucinating schizophrenia, autism spectrum disorder, epilepsy, chronic fatigue syndrome, chronic tinnitus, and other diseases can also lead to changes in the fractional anisotropy value of arcuate fasciculus; however, different studies have different conclusions about how this change occurs. To obtain a better understanding, more clinical studies are required. Owing to various advancements in neuroimaging, a better understanding and identification of vital targets for restoration of neurological function are possible. The arcuate fasciculus is stratified into three substructures, each having unique neurological functions. Both diffusion tensor imaging (DTI) sequences and deterministic monitoring techniques render it possible to visually and quantitatively analyze the substructure in three parts. In this review, we examined the progress of the arcuate fasciculus and quantitative DTI technology in recent years.

Colchicine (Col) is used to prevent and treat acute gout flare; however, its therapeutic use is strictly limited owing to severe gastrointestinal side effects after oral administration. Therefore, we developed a dissolvable Col-loaded microneedle (MN) with hyaluronic acid to deliver Col via the transdermal route. We studied the preparation, mechanical properties, skin insertion, skin irritation, drug content, and transdermal release of the Col-loaded MN. The pharmacokinetics of Col after Col-loaded MN application were compared with those of Col solution gavage over 24 h. Knee joint edema evaluation and the hindfoot mechanical threshold test were conducted to determine the pharmacodynamic profile. The dissolvable Col-loaded MN possessed sufficient mechanical strength to penetrate the skin and release the loaded drug. No skin irritation was observed for 3 days after application. We found that 3.36-fold more Col contained in MNs was delivered through the skin compared with that in gel in vitro, and moderate relative bioavailability in vivo. The Col-loaded MN significantly relieved swollen knee joints and mechanical hypernociception in an acute gout model in rats. The dissolvable Col-loaded MN array reduced inflammation and pain via topical administration when acute gout occurred. Reducing the gastrointestinal side effects of Col-loaded MNs is expected to optimize the therapeutic effects of Col and improve patient compliance.

Abstract Background Carbon monoxide (CO) is an important signaling molecule participating in multiple biological functions. Previous studies have confirmed the valuable roles of CO in cancer therapies. If the CO concentration and distribution can be controlled in tumors, new cancer therapeutic strategy may be developed to benefit the patient survival. Results In this study, a UiO-67 type metal–organic framework (MOF) nanoplatform was produced with cobalt and ruthenium ions incorporated into its structure (Co/Ru-UiO-67). Co/Ru-UiO-67 had a size range of 70–90 nm and maintained the porous structure, with cobalt and ruthenium distributed uniformly inside. Co/Ru-UiO-67 was able to catalyze carbon dioxide into CO upon light irradiation in an efficient manner with a catalysis speed of 5.6 nmol/min per 1 mg Co/Ru-UiO-67. Due to abnormal metabolic properties of tumor cells, tumor microenvironment usually contains abundant amount of CO2. Co/Ru-UiO-67 can transform tumor CO2 into CO at both cellular level and living tissues, which consequently interacts with relevant signaling pathways (e.g. Notch-1, MMPs etc.) to adjust tumor microenvironment. With proper PEGylation (pyrene-polyacrylic acid-polyethylene glycol, Py-PAA-PEG) and attachment of a tumor-homing peptide (F3), functionalized Co/Ru-UiO-67 could accumulate strongly in triple-negative MDA-MB-231 breast tumors, witnessed by positron emission tomography (PET) imaging after the addition of radioactive zirconium-89 (89Zr) into Co-UiO-67. When applied in vivo, Co/Ru-UiO-67 could alter the local hypoxic condition of MDA-MB-231 tumors, and work synergistically with tirapazamine (TPZ). Conclusion This nanoscale UiO-67 MOF platform can further our understanding of CO functions while produce CO in a controllable manner during cancer therapeutic administration. Graphical Abstract

Abstract In this study, four varieties of rice were cultivated on the same farmland under same conditions and for same duration. However, their lodging resistance was found to be obviously different from each other. Herein, three key factors that highly influenced the lodging resistance were identified. First, in terms of morphological trait, in contrast to the generally believed theory that the overall thickness of the fresh culm wall governs the strength, the thickness of the depressed region of the dried basal culm wall largely determined the mechanical properties by acting as the weak link. This depressed region represents the vulnerable part with high syneresis rate. Second, the culm and its carbon framework exhibited sufficient strength and rigidity for both support and stability of the rice stem. The constraint of high lodging resistance of rice plants is attributed to the culm flexibility. Furthermore, the results of the positron annihilation lifetime spectroscopy corroborate that the most amorphous part and the highest-fraction free volume in the culm carbon framework were found for samples that exhibited high lodging resistance. This result confirmed the significant influence of the culm flexibility on lodging resistance. Third, a higher level of nitrogen element content in the basal culm can benefit its growth and development, which may contribute to an increase in lodging resistance of rice plants.

Background: Enhanced Recovery After Surgery (ERAS) has been used to improve surgical outcomes in recent years. However, its safety and efficacy in elderly patients with gastric cancer remain unclear. The aim of this study was to reveal the safety and efficacy of the ERAS protocol in elderly patients with gastric cancer. Methods: Elderly gastric cancer patients (age≥70 years) who underwent gastrectomy were divided into the ERAS group and the conventional group. Postoperative complications, postoperative hospital stay, hospitalization expenses, and readmission rates were compared between the two groups. Results: From December 2019 to January 2021, 100 eligible patients were enrolled in our study. All baseline data were balanced between the ERAS group and the conventional group. There was no significant difference in terms of complications (18% vs. 16%, P = 0.14) between the two groups. The most common complication was pneumonia. Four patients were observed in the conventional group and three patients in the ERAS group. The postoperative hospital stay was shorter in the ERAS group (8.2 vs. 10.4, P = 0.001). Conclusions: The ERAS protocol could be safely used in elderly gastric cancer patients undergoing gastrectomy and shorten postoperative hospital stay.

Abstract Hyperspectral imaging has broad applications and impacts in areas including environmental science, weather, and geo/space exploration. The intrinsic spectral–spatial structures and potential multi-level features in different frequency bands make multilayer graph an intuitive model for hyperspectral images (HSI). To study the underlying characteristics of HSI and to take the advantage of graph signal processing (GSP) tools, this work proposes a multilayer graph spectral analysis for hyperspectral images based on multilayer graph signal processing (M-GSP). More specifically, we present multilayer graph (MLG) models and tensor representations for HSI. By exploring multilayer graph spectral space, we develop MLG-based methods for HSI applications, including unsupervised segmentation and supervised classification. Our experimental results demonstrate the strength of M-GSP in HSI processing and spectral–spatial information extraction.

Ongoing shifts in climate, especially extreme drought, is posing considerable threats to the forest carbon uptake worldwide. In China, summer 2022 was the warmest and driest since the beginning of meteorological measurements. This study synthesized the tower-based carbon fluxes and climate data from two subtropical evergreen and deciduous forest ecosystems to investigate the effects of such summer drought. Interestingly, the net ecosystem production (NEP = −NEE) only exhibited a slight decrease at the deciduous forest while it even enhanced at the evergreen forest during the summer 2022 drought. Further analysis revealed that although reductions in gross primary productivity (GPP) and ecosystem respiration ( R _e ) were found at both sites, larger decrease in R _e than GPP at the evergreen forest led to stronger NEP compared to the previous year. However, the NEP of two forest ecosystems sharply reduced in the following 2023, which can be ascribed to the legacy effects of the summer 2022 drought. The results of multiple linear regression revealed that soil water content (SWC) was recognized as the primary driver of GPP and R _e , and downwelling shortwave radiation ( R _g ) regulated the variability of NEP during the summer 2022. Across these forest carbon fluxes including GPP, R _e and NEP, the deciduous forest exhibited larger resistance, whereas the evergreen forest showed stronger resilience. All analyses emphasized the diverse adaptive strategies among vegetation types, which acted an important role in assessing ecosystem carbon sequestration in face of future climate change.

Accurate prediction of shield tunneling-induced settlement is a complex problem that requires consideration of many influential parameters. Recent studies reveal that machine learning (ML) algorithms can predict the settlement caused by tunneling. However, well-performing ML models are usually less interpretable. Irrelevant input features decrease the performance and interpretability of an ML model. Nonetheless, feature selection, a critical step in the ML pipeline, is usually ignored in most studies that focused on predicting tunneling-induced settlement. This study applies four techniques, i.e. Pearson correlation method, sequential forward selection (SFS), sequential backward selection (SBS) and Boruta algorithm, to investigate the effect of feature selection on the model's performance when predicting the tunneling-induced maximum surface settlement (Smax). The data set used in this study was compiled from two metro tunnel projects excavated in Hangzhou, China using earth pressure balance (EPB) shields and consists of 14 input features and a single output (i.e. Smax). The ML model that is trained on features selected from the Boruta algorithm demonstrates the best performance in both the training and testing phases. The relevant features chosen from the Boruta algorithm further indicate that tunneling-induced settlement is affected by parameters related to tunnel geometry, geological conditions and shield operation. The recently proposed Shapley additive explanations (SHAP) method explores how the input features contribute to the output of a complex ML model. It is observed that the larger settlements are induced during shield tunneling in silty clay. Moreover, the SHAP analysis reveals that the low magnitudes of face pressure at the top of the shield increase the model's output.

It remains challenging to accurately classify complicated clouds owing to the various types of clouds and their distribution on multiple layers. In this paper, multi-band radiation information from the geostationary satellite Himawari-8 and the cloud classification product of the polar orbit satellite CloudSat from June to September 2018 are investigated. Based on sample sets matched by two types of satellite data, a random forest (RF) algorithm was applied to train a model, and a retrieval method was developed for cloud classification. With the use of this method, the sample sets were inverted and classified as clear sky, low clouds, middle clouds, thin cirrus, thick cirrus, multi-layer clouds and deep convection (cumulonimbus) clouds. The results indicate that the average accuracy for all cloud types during the day is 88.4%, and misclassifications mainly occur between low and middle clouds, thick cirrus clouds and cumulonimbus clouds. The average accuracy is 79.1% at night, with more misclassifications occurring between middle clouds, multi-layer clouds and cumulonimbus clouds. Moreover, Typhoon Muifa from 2022 was selected as a sample case, and the cloud type (CLT) product of an FY-4A satellite was used to examine the classification method. In the cloud system of Typhoon Muifa, a cumulonimbus area classified using the method corresponded well with a mesoscale convective system (MCS). Compared to the FY-4A CLT product, the classifications of ice-type (thick cirrus) and multi-layer clouds are effective, and the location, shape and size of these two varieties of cloud are similar.

Surface settlements caused by twin tunneling are a major interest in underground space engineering. Most prevailing studies have investigated the surface settlements observed over twin tunnels constructed in clay. Yet, less attention is given to the twin tunnels excavated in silty sand, which is the focus of this study. A comprehensive field monitoring scheme was designed in the Hangzhou metro line six project to measure the surface settlements during twin tunneling by adopting earth pressure balance shields. The influence of four shield operational parameters, namely, face pressure, tail grouting pressure, penetration rate, and pitching angle on the surface settlements due to twin tunneling are explored. In general, the total settlement profiles observed over twin tunnels follow an inverted bimodal shape. The post-settlement observed over the 1st tunnel due to the 2nd tunnel excavation is non-trivial when the twin tunnels are spaced closely. Low face pressure and tail grouting pressure can induce excessive peak surface settlements during twin tunneling in silty sand.

PurposeThe study aims to assess the incidence of short-term patient-reported postoperative gastrointestinal symptoms (PGISs) after gastric cancer surgery and explore the relative risk factors for the symptoms.MethodsPatients with radical gastrectomy were included for this retrospective and observational study. Symptoms extracted from the MD Anderson Symptom Inventory Gastrointestinal Cancer Module (MDASI-GI) were collected in postdischarge week (PDW) 1 and postoperative month (POM) 1. The distributing states of symptoms were analyzed in PDW1 and POM1. Logistic regression models were used to identify risk factors for PGISs.ResultsAmong 356 patients with complete interviews, 156 (43.8%) patients reported abdominal distention in PDW1, which was significantly higher than patients in POM1 [103 (28.9%), p < 0.001]. Pain (15.2% vs. 9.8%), dysphagia (5.6% vs. 7.0%), diarrhea (3.7% vs. 3.4%), and vomiting (2.5% vs. 2.8%) had no significant differences between PDW1 and POM1. Logistic models found that risk factors for PGISs were total gastrectomy [odds ratio (OR): 1.948; 95% CI: 1.097–3.459; p = 0.023] and disturbed sleep (OR: 3.116; 95% CI: 1.831–5.303; p < 0.001) in PDW1 and female gender (OR: 1.726; 95% CI: 1.071–2.782; p = 0.025), total gastrectomy (OR: 1.729; 95% CI: 1.055–2.834; p = 0.030), and disturbed sleep (OR: 3.533; 95% CI: 1.757–7.106; p < 0.001) in POM1.ConclusionsThe main symptom after gastric cancer surgery was abdominal distention. The relative risk factors for gastrointestinal symptoms after gastric cancer surgery were total gastrectomy and disturbed sleep. Timely symptom intervention may improve the quality of life of postgastrectomy patients.

Global climate change, especially extreme drought events, presents a complicated challenge to humanity and Earth’s system in the 21st century. As an extremely important carbon sink region in China, Southwest China has encountered frequent drought disasters in recent decades. It is critical to explore the frequency, duration, severity, and other associated characteristics of drought events as well as their spatial and temporal patterns in the region from a long-term perspective. In this study, we used the latest dataset from the Spanish National Research Council (CSIC) between 1901 and 2018 to extract all drought events by calculating the standardized anomaly of the Standardized Precipitation Evapotranspiration Index (SPEI). Theil–Sen median trend analysis, the Mann–Kendall test, and the moving t-test were used to reveal the spatial trend and mutation point of drought severity. The results showed that (1) The standardized anomaly of the 3-month SPEI can accurately identify drought events in Southwest China. In total, 72 drought events occurred during this period, of which the consecutive drought in autumn, winter, and spring from 2009 to 2010 lasted the longest, having the most substantial severity and the most extensive damage range. (2) Drought events mainly started in spring and early summer and ended in autumn and winter. The distribution of drought was the most expansive and the drought severity was the most serious in September. (3) In terms of spatial pattern, Guangxi has the highest frequency of drought events, with some areas experiencing up to 100 events. The average duration of drought events ranged between 3.5 and 5.5 months, with most lasting for 4–5 months. The most severe drought areas are mainly concentrated in southern Sichuan and western Yunnan. Overall, the severity of drought events in the west were generally higher compared to that in the east. (4) Over the past 120 years, most of the region (82.46%) showed an increasing trend in drought severity, with a slope of up to −0.01. About 15.12% of the areas exhibited a significant drying trend (p < 0.05), particularly in southern Sichuan, eastern Guizhou, and northern and southern Yunnan. Such analyses can serve as a scientific foundation for developing drought prevention and mitigation measures as well as exploring how drought events affect the structure and function of terrestrial ecosystems in Southwest China.

Preoperative nutrition and inflammation are closely related to tumors (T). Many hematological marker assessment tools comprise nutritional and systemic inflammatory indexes, evaluating essential factors for cancer nutrition, growth, and progression. This study retrospectively investigated whether the C-reactive protein (CRP)-to-lymphocyte ratio (CLR) could predict lymphovascular invasion (LVI) in gastric cancer (GC) patients based on their nutritional status. We included 262 patients who underwent GC surgery between 2019 and 2020. The patient's nutritional status was assessed using the Patient-Generated Subjective Global Assessment (PG-SCA), and patients with scores ≥4 were classified as malnourished. First, we examined 7 hematological marker combinations using receiver operating characteristic (ROC) curves to determine which one best predicted malnutrition. The CLR predicted malnutrition more accurately than other ratios (area under the curve: 0.62, 95% confidence interval [CI]: 0.55-0.69, P = .002); the optimal cut-off value for malnutrition was 1.04. Next, we evaluated the relationship between the 7 combinations and postoperative LVI. A CLR higher than 1.04 (odds ratio [OR]: 1.81, 95% CI: 1.09-3.00, P = .021) and a platelet-to-lymphocyte ratio (PLR) higher than 129.00 (OR: 1.64, 95% CI: 1.00-2.67, P = .049) were associated with LVI in the univariate analysis, and the CLR was an independent predictor of LVI in the multivariate analysis (OR: 1.73, 95% CI: 1.04-2.87, P = .036). The preoperative CLR can assess nutritional status and independently predict LVI in GC.

Abstract Background Proximal gastrectomy with double-tract reconstruction (DTR) has been used for upper third gastric cancer as a function-preserving procedure. However, the safety and feasibility of laparoscopic proximal gastrectomy (LPG) with DTR remain uncertain. This study compared open proximal gastrectomy (OPG) with DTR and LPG with DTR for proximal gastric cancer. Methods Sixty-four patients who had undergone OPG with DTR and forty-six patients who had undergone LPG with DTR were enrolled in this case–control study. The clinical characteristics, surgical outcomes and postoperative nutrition index were analysed retrospectively. Results The operation time was significantly longer in the LGP group than in the OPG group (258.3 min vs 205.8 min; p = 0.00). However, the time to first flatus and postoperative hospital stay were shorter in the LPG group [4.0 days vs 3.5 days (p = 0.00) and 10.6 days vs 9.2 days (p = 0.001), respectively]. No significant difference was found between the two groups in the number of retrieved lymph nodes, complications or reflux oesophagitis. The nutrition status was assessed using the haemoglobin, albumin, prealbumin and weight levels from pre-operation to six months after surgery. No significant difference was found between the groups. Conclusion LPG with DTR can be safely performed for proximal gastric cancer patients by experienced surgeons.

Recently a large number of 3D object tracking methods have been extensively investigated and applied in a variety of applications using convolutional neural networks. Although most of them have made great progress in partial occlusion, the intricate interweaving of moving agents (e.g. pedestrians and vehicles) may lead to inferior performance of 3D object tracking in complex traffic scenes. To boost the performance of 3D object tracking in cases of severe occlusions, we present an end-to-end deep learning framework with a driving behavior-aware model that takes full advantage of spatial-temporal details in consecutive frames and learns the driving behavior from object variations in 2D center point, depth, rotation and translation in parallel. In contrast to prior work, our novelty formulates driving behavior that reasons about the possible motion trajectories of the investigated target for autonomous systems. We show in experiments that our method outperforms state-of-the-art approaches on 3D object tracking in the challenging nuScenes dataset.

Tunneling-induced ground surface settlement is associated with many complex influencing factors. Beyond factors related to tunnel geometry and surrounding geological conditions, operational factors related to the shield machine are highly significant because of the complexity of shield-soil interactions. Distinguishing the most relevant factors can be very difficult, for all factors seem to affect tunneling-induced settlement to some degree, with none clearly the most influential. In this research, a machine learning method is adopted to intelligently select features related to tunneling-induced ground settlement based on measured data and form a robust non-parametric model with which to make a prediction. The recorded data from a real construction site were compiled and 12 features related to the operational factors were summarized. Using the intelligent method, two other features in addition to cover depth–pitching angle and rolling angle–were distinguished from among the 12 feature candidates as those most influencing the settlement trough. Another new finding is that advance rate does not emerge in the top 10 selected models from the observational data used. The generated non-parametric model was validated by comparing the measured data from the testing dataset and performance on a new dataset. Sensitivity analysis was conducted to evaluate the contribution of each factor. According to the results, engineers in general practice should attend closely to pitching angle during tunnel excavation in soft soil conditions.

Abstract Background Grassland ecosystems play an important role in the terrestrial carbon cycles through carbon emission by ecosystem respiration (R e ) and carbon uptake by plant photosynthesis (GPP). Surprisingly, given R e occupies a large component of annual carbon balance, rather less attention has been paid to developing the estimates of R e compared to GPP. Results Based on 11 flux sites over the diverse grassland ecosystems in northern China, this study examined the amounts of carbon released by R e as well as the dominant environmental controls across temperate meadow steppe, typical steppe, desert steppe and alpine meadow, respectively. Multi-year mean R e revealed relatively less CO2 emitted by the desert steppe in comparison with other grassland ecosystems. Meanwhile, C emissions of all grasslands were mainly controlled by the growing period. Correlation analysis revealed that apart from air and soil temperature, soil water content exerted a strong effect on the variability in R e , which implied the great potential to derive R e using relevant remote sensing data. Then, these field-measured R e data were up-scaled to large areas using time-series MODIS information and remote sensing-based piecewise regression models. These semi-empirical models appeared to work well with a small margin of error (R 2 and RMSE ranged from 0.45 to 0.88 and from 0.21 to 0.69 g C m−2 d−1, respectively). Conclusions Generally, the piecewise models from the growth period and dormant season performed better than model developed directly from the entire year. Moreover, the biases between annual mean R e observations and the remotely-derived products were usually within 20%. Finally, the regional R e emissions across northern China’s grasslands was approximately 100.66 Tg C in 2010, about 1/3 of carbon fixed from the MODIS GPP product. Specially, the desert steppe exhibited the highest ratio, followed by the temperate meadow steppe, typical steppe and alpine meadow. Therefore, this work provides a novel framework to accurately predict the spatio-temporal patterns of R e over large areas, which can greatly reduce the uncertainties in global carbon estimates and climate projections.

With the tremendous growth in mobile data traffic, wireless cellular networks are facing a rigorous challenge to increase network capacity. Despite that many advanced technologies are used, the shortage of spectrum resource is still the main bottleneck for capacity enhancement. To address the challenge, the cellular networks have been motivated to seek for more fruitful radio spectra. Amongst many others, the unlicensed 5 GHz spectrum is a promising candidate due to its low channel attenuation, large available bandwidth, and easy to utilize. Therefore, the innovative technology of long-term evolution (LTE) using the unlicensed spectrum, known as LTE-Unlicensed (LTE-U), has been widely investigated as a promising means to increase the data rate of cellular networks. The unique characteristics of the unlicensed spectrum bring new challenges to resource management in the LTE-U system. During the last few years, there have been a lot of resource management designs for the newly-born but vigorous LTE-U technologies. This paper provides a comprehensive overview of the state-of-the-art resource management scenarios in LTE-U systems, including single small cell base station (SBS), multiple SBSs, device-to-device (D2D) networks, vehicular networks, and unmanned aerial vehicle (UAV) systems. The future research issues of resource management in LTE-U for 5G are also outlined.

The jacking force is one of the important parameters affecting the construction process in the vertical tunnelling method. To study the dynamic changing process of jacking force with the jacked distance and the influencing factors of the maximum jacking force, both the indoor model test and numerical simulation were conducted. In the model test, we investigated the influence of the height of the soil and water content. The results indicated that the higher the overburden height was, the greater the jacking force. Moreover, the water content enhanced the compressibility of the soil and had little effect on the maximum jacking force. Additionally, the coupled Eulerian–Lagrangian (CEL) approach was used to simulate the vertical jacking construction. In the numerical simulation, we investigated two construction factors (jacking speed and the standpipe outer diameter) and four soil parameters (cohesion, internal friction angle, elastic modulus, and Poisson’s ratio). Before that, the CEL simulation results were compared with test data to prove the rationality of the CEL approach, and the two were in good agreement. The results showed that among the six influence parameters, according to the influence degree on the maximum jacking force from large to low, the outer diameter of the standpipe, internal friction angle, cohesion, elastic modulus, jacking speed, and Poisson’s ratio were ranked. In addition, the jacking speed of numerical analysis was suggested to be 0.2 m/s. The research results in this paper can provide a reference for the construction of the vertical tunnelling method.

Based on the linear superposition of the quadrilateral isoparametric membrane element and quadrilateral Mindlin plate element, basic vector formulas for the quadrilateral isoparametric shell element with the shear deformation is derived. Two different coordinate modes for updating the particle displacement and the element node internal force are put forward. The uniform numerical solution for an irregular quadrilateral element is realized by the isoparametric integral scheme along the element plane. Then, the bilinear elastoplastic constitutive of material is introduced into the vector finite shell element, and the nonlinear effect of the material is realized based on the integral method along the thickness. On this basis, the nonlinear calculation and analysis program of the quadrilateral isoparametric shell element is developed. Numerical example results show that the static and dynamic analysis, large deformation and large rotation analysis, and buckling analysis can all be well performed for the shell structures by the developed program, which verifies the validity of theoretical derivation and computer program.

In this study, the field measurement was conducted on the twin shield tunnelling in a shield section of Hangzhou Metro Line 6, where the surface deformation caused by twin shield tunnelling in the silty sand was obtained. The surface deformation law and the applicability of the twin-line Peck formula in the silt area were analyzed. The relationship between the cutterhead torque and the surface deformation in the silty sand was identified. Furthermore, the differences in surface deformation of twin shield tunnelling in the Hangzhou soft soil area were discussed. The results show that the settlement process caused by twin shield tunnelling in silty sand is faster than that of soft soil and has no rebound phenomenon. The twin-line Peck formula is suitable in silty sand, but the prediction of the latter line using this formula is slightly deviated because of the secondary disturbance effect. Due to the secondary disturbance of the soil caused by the construction of the latter line, the soil loss rate of the latter line is higher than that of the former line. Therefore, the reference ratio of the soil loss rate of the latter line and the former line is given. Furthermore, the cutterhead torque of the shield machine was found to be associated with the maximum instantaneous value of the surface deformation.

The bearing capacity of the vertical underpinning structure system is the key index in the design of top-down construction for adding a basement layer under existing buildings. The influence of the lateral restraint is the most significant under the dynamic construction excavation. For the problem of the bearing capacity of the existing engineering pile group under the top-down construction, the linear eigenvalue stability method was used first to study the influence of the lateral restraints such as the horizontal resistance of soil, the diameter of piles body, and the bending rigidity of the temporary steel bracing on its bearing capacity. The corresponding critical stability load and the effective length coefficient were then obtained. Then, based on the nonlinear extreme point stability method with the initial geometrical imperfection, the amplification range for the effective length coefficient was studied. Finally, based on the current Chinese Code Formula (JGJ 94-2008) and considering the influence of the compression buckling effect of the high cap pile, the present solution of the bearing capacity for the pile body was obtained and compared with the code solution. It turns out that the nonlinear bearing capacity of existing engineering piles group with initial imperfection is smaller than the critical stability load of the linear eigenvalue and increases with the increase of the imperfection amplitude, and the amplification range of the effective length coefficient is 1.10∼1.20. The present solution of the bearing capacity with the compression buckling effect is 1.10∼1.30 times of the code solution, which shows that the code solution is partial to safety, and the residual bearing can be properly considered in the design.

Land surface temperature (LST) is a key parameter in the study of surface energy balance and climate change from local through to global scales. Vegetation has inevitably influenced the LST by changing the surface properties. However, the thermal environment pattern in the Yangtze River Basin (YRB) still remains unclear after the implementation of large-scale ecological restoration projects. In this study, the temporal and spatial variation characteristics of LST were analyzed based on the Theil–Sen estimator, Mann–Kendall trend analysis and Hurst exponent from 2003 to 2021. The relationships between vegetation and LST were further revealed by using correlation analysis and trajectory-based analysis. The results showed that the interannual LST was in a state of fluctuation and rise, and the increasing rate at night time (0.035 °C·yr−1) was faster than that at day time (0.007 °C·yr−1). An obvious cooling trend could be identified from 2007 to 2012, followed by a rapid warming. Seasonally, the warming speed was the fastest in summer and the slowest in autumn. Additionally, it was found that autumn LST had a downward trend of 0.073 °C·yr−1 after 2015. Spatially, the Yangtze River Delta, Hubei province, and central Sichuan province had a significant warming trend in all seasons, except autumn. The northern Guizhou province and Chongqing showed a remarkable cooling trend only in autumn. The Hurst exponent results indicated that the spring LST change was more consistent than the other three seasons. It was found by studying the effect of land cover types on LST changes that sparse vegetation had a more significant effect than dense vegetation. Vegetation greening contributed 0.0187 °C·yr−1 to the increase in LST in winter, which was spatially concentrated in the central region of the YRB. For the other three seasons, vegetation greening slowed the LST increase, and the degree of the effect decreased sequentially in autumn, summer, spring and winter. These results improve the understanding of past and future variations in LST and highlight the importance of vegetation for temperature change mitigation.

Large-scale Ecosystem Restoration Projects (ESPs) have been launched to restore vegetation and increase carbon stocks across China. Whether these ESPs could mitigate the loss of carbon emission due to vegetation degradation caused by human disturbances, such as urban expansion, remains unclear. In this study, we analysed the major human-driven land use and land cover change (LUCC) and evaluated their impacts on gross primary productivity (GPP) dynamics in Southwest China during 2001–2015. Results showed that afforestation, agricultural reclamation, urban expansion and grass planting were the major LUCC. Afforestation accounted for approximately 52% of the LUCC area and greatly contributed to the GPP increase, particularly the multiyear accumulative GPP (5.26 Tg C) in the whole area. Urban expansion only accounted for 20% of the LUCC area and led to the decrease of multiyear accumulative GPP (2.52 Tg C) in the whole area. In terms of legacy effect, afforestation mitigated the GPP decrease caused by urban expansion. However, the urban expansion rate (~15.01% per year) was much faster than that of afforestation (~0.13% per year). Therefore, urban expansion might offset more GPP increase from afforestation in the future. Hence, an effective regulation of urban expansion whilst strengthening conservation efforts is urgently needed to enhance vegetation cover and C stock in Southwest China.

The relentless growth of wireless applications and data traffic continues to accentuate the long felt need for decentralized, self-managed, and cooperative network architectures. Enlightened by the power of blockchain technology, we propose a blockchain radio access network (B-RAN) architecture and develop decentralized, secure, and efficient mechanisms to manage network access and authentication among inherently trustless network entities. We further identify promising advanced functions made possible by adopting blockchain for open radio access networks. Our test results demonstrate the benefits of the B-RAN architecture. We also present a number of challenges and future research directions.

Based on the lateral consolidation compression experiment of remolded soil simulating the effects of pile driving and soil squeezing, in this paper, the microstructures of soil with different degrees of lateral consolidation were investigated by a scanning electron microscope. Combined with Image-Pro Plus software to process data, parameters such as the equivalent diameter, porosity, circularity, directional frequency and fractal dimension of the soil microstructure were analyzed. The results demonstrate that the microstructure of the soil sample before consolidation was debris, aggregated particles and irregular flake aggregates. Following consolidation, the microstructure became a closed flake structure, where an obvious agglomeration phenomenon occurred. During the process of lateral consolidation compression, the large pore structure was more likely to be compressed and damaged, resulting in a decrease in the equivalent pore diameter and plane porosity, the approaching of circularity towards unity and an increase in the compaction and homogenization of soil with obvious directionality. Soil particles moved continuously under the action of consolidation compression to adjust the microstructure, and the fractal dimension gradually increased. Then, as consolidation compression continued, it gradually developed to a new equilibrium state, where the fractal dimension began to decrease and approach stability.

The stress-strain characteristics of soil depend primarily on the previous stress history and stress path, thus related to both the stress magnitude and direction. To have a better understanding of the response of soft clay under heart-shaped stress paths, 18 cyclic hollow cylinders tests were performed on undisturbed Hangzhou soft clay under different cyclic stress ratios, deviatoric consolidation ratios (K0), and loading frequencies. The result shows that as the vertical dynamic stress amplitude, K0 value, and loading frequency increase, the degradation index gradually decreases. Moreover, the degradation index of the soil under the cyclic torsion shear (CTS) test is always higher than that under the cyclic triaxial (CT) test. The increase in the amplitude of the cyclic stress ratio (CSR), K0 value, and the decrease in the loading frequency will promote the initial accumulative plastic strain and accelerate the failure rate of the soil sample; it shows that the effects of cyclic stress ratio amplitude, deviatoric consolidation ratios K0, and loading frequency on the accumulative plastic deformation of soil cannot be ignored. On the basis of the test results, a logarithmic relationship between the degradation index and the loading frequency is determined. A new empirical formula of accumulative plastic strain degradation of soft clay has been established, and its accuracy has been further verified by test data. The research results can provide theories for predicting and calculating the long-term settlement and deformation of clay foundation.

This paper is based on the case of the earth pressure balance (EPB) shield tunnelling project of the new Metro Line 2 undercrossing the existing Metro Line 1 in the soft soil urban area of Hangzhou. Because the EPB shield must break through a plain concrete wall before undercrossing the existing tunnels, the pipe roof prereinforcement was adopted to stabilize the soil between the existing tunnels and the new shield tunnel. The deformation characteristics of the existing tunnels in the process of double shield undercrossing were discussed. According to the variation of shield position, the settlement development could be divided into three stages: shield approaching subsidence, shield crossing heave, and shield leaving subsidence. The horizontal displacement shows a back and forth variation characteristic consistent with the direction of shield tunnelling. At the junction of tunnel and station, the shield undercrossing caused considerable differential settlement between the existing tunnel and the station. The construction of pipe roof prereinforcement will lead to the presettlement of the existing tunnels. The settlement of the existing tunnels caused by the attitude deviation of pipe roof and grouting disturbance should be reduced in reasonable ranges. In addition, the maximum longitudinal settlement of the existing tunnel during the shield second undercrossing was also discussed. It was considered that the influence of wall breaking is greater than the sequence of shield undercrossing. The driving parameters of shield tunnelling should be optimized before the second crossing.