Numerical investigation of geostress influence on the grouting reinforcement effectiveness of tunnel surrounding rock mass in fault fracture zones

Grouting is a widely used approach to reinforce broken surrounding rock mass during the construction of underground tunnels in fault fracture zones,and its reinforcement effectiveness is highly affected by geostress.In this study,a numerical manifold method(NMM)based simulator has been developed to examine the impact of geostress conditions on grouting reinforcement during tunnel excavation.To develop this simulator,a detection technique for identifying slurry migration channels and an improved fluid-solid coupling(FeS)framework,which considers the influence of fracture properties and geostress states,is developed and incorporated into a zero-thickness cohesive element(ZE)based NMM(Co-NMM)for simulating tunnel excavation.Additionally,to simulate coagulation of injected slurry,a bonding repair algorithm is further proposed based on the ZE model.To verify the accuracy of the proposed simulator,a series of simulations about slurry migration in single fractures and fracture networks are numerically reproduced,and the results align well with analytical and laboratory test results.Furthermore,these numerical results show that neglecting the influence of geostress condition can lead to a serious over-estimation of slurry migration range and reinforcement effectiveness.After validations,a series of simulations about tunnel grouting reinforcement and tunnel excavation in fault fracture zones with varying fracture densities under different geostress conditions are conducted.Based on these simula-tions,the influence of geostress conditions and the optimization of grouting schemes are discussed.

Study on damage-stress loss coupling model of rock and prestressed anchor cable in dry-wet environment

The loss of anchoring force is one of the problems to be solved urgently.The anchorage loss is a key factor causing the failure of anchoring engineering,so it is crucial to study the time-dependent variation of anchoring force.Alternating dry and wet(D-W)conditions have a significant effect on deformation of rock.The anchoring system is composed of anchoring components and rock mass,and thus rock deformation has a significant impact on the loss of anchoring force.Quantifying rock deformation under the effects of D-W cycles is a prerequisite to understanding the factors that influence loss of anchoring force in anchor bolts.In this study,we designed an anchoring device that enabled real-time monitoring of the variation in strain during D-W periods and rock testing.Nuclear magnetic resonance(NMR)measurements showed that under D-W conditions,the increment in porosity was smaller for prestressed rock than unstressed rock.The trends of prestress loss and strain variation are consistent,which can be divided into three characteristic intervals:rapid attenuation stage,slow attenuation stage and relatively stable stage.At the same stress level,the rate of stress loss and strain for the soaking specimen was the highest,while that of the dried specimen was the lowest.In the same D-W cycling conditions,the greater the prestress,the smaller the strain loss rate of the rock,especially under soaking conditions.The characteristics of pore structure and physical mechanical parameters indicated that prestress could effectively suppress damage caused by erosion related to D-W cycles.The study reveals the fluctuation behavior of rock strain and prestress loss under D-W conditions,providing a reference for effectively controlling anchoring loss and ideas for inventing new anchoring components.

CsXDH1 gene promotes caffeine catabolism induced by continuous strong light in tea plant

Tea plant(Camellia sinensis)is an important cash crop with extensive adaptability in the world.However,complex environmental factors force a large variation of tea quality-related components.Caffeine is essential for the formation of bitter and fresh flavors in tea,and is the main compound of tea that improves human alertness.Continuous strong light stimulation was observed to cause caffeine reduction in tea leaves,but the mechanism is not clear.In this study,the response of tea plant to light intensity was analysed mainly by multi-omics association,antisense oligodeoxynucleotide(asODN)silencing technique,and in vitro enzyme activity assay.The results revealed multiple strategies for light intensity adaptation in tea plant,among which the regulation of chloroplasts,photosynthesis,porphyrin metabolism,and resistance to oxidative stress were prominent.Caffeine catabolism was enhanced in continuous strong light,which may be a light-adapted strategy due to strict regulation by xanthine dehydrogenase(XDH).asODN silencing and enzymatic activity assays confirmed that CsXDH1 is a protein induced by light intensity to catalyze the substrate xanthine.CsXDH1 asODN silencing resulted in significant up-regulation of both caffeine and theobromine in in vitro enzyme activity assay,but not in vivo.CsXDH1 may act as a coordinator in light intensity adaptation,thus disrupting this balance of caffeine catabolism.

Spatial gradient distributions of thermal shock-induced damage to granite

In this study,we attempted to investigate the spatial gradient distributions of thermal shock-induced damage to granite with respect to associated deterioration mechanisms.First,thermal shock experiments were conducted on granite specimens by slowly preheating the specimens to high temperatures,followed by rapid cooling in tap water.Then,the spatial gradient distributions of thermal shock-induced damage were investigated by computed tomography(CT)and image analysis techniques.Finally,the influence of the preheating temperature on the spatial gradients of the damage was discussed.The results show that the thermal shock induced by rapid cooling can cause more damage to granite than that induced by slow cooling.The thermal shock induced by rapid cooling can cause spatial gradient distributions of the damage to granite.The damage near the specimen surface was at a maximum,while the damage inside the specimen was at a minimum.In addition,the preheating temperature can significantly influence the spatial gradient distributions of the thermal shock-induced damage.The spatial gradient distribution of damage increased as the preheating temperature increased and then decreased significantly over 600
C.When the preheating temperature was sufficiently high(e.g.800
C),the gradient can be ignored.

Real-time rock mass condition prediction with TBM tunneling big data using a novel rock-machine mutual feedback perception method

Real-time perception of rock mass information is of great importance to efficient tunneling and hazard prevention in tunnel boring machines(TBMs).In this study,a TBM-rock mutual feedback perception method based on data mining(DM) is proposed,which takes 10 tunneling parameters related to surrounding rock conditions as input features.For implementation,first,the database of TBM tunneling parameters was established,in which 10,807 tunneling cycles from the Songhua River water conveyance tunnel were accommodated.Then,the spectral clustering(SC) algorithm based on graph theory was introduced to cluster the TBM tunneling data.According to the clustering results and rock mass boreability index,the rock mass conditions were classified into four classes,and the reasonable distribution intervals of the main tunneling parameters corresponding to each class were presented.Meanwhile,based on the deep neural network(DNN),the real-time prediction model regarding different rock conditions was established.Finally,the rationality and adaptability of the proposed method were validated via analyzing the tunneling specific energy,feature importance,and training dataset size.The proposed TBM-rock mutual feedback perception method enables the automatic identification of rock mass conditions and the dynamic adjustment of tunneling parameters during TBM driving.Furthermore,in terms of the prediction performance,the method can predict the rock mass conditions ahead of the tunnel face in real time more accurately than the traditional machine learning prediction methods.

Bounding surface plasticity model for stress-strain and grain-crushing behaviors of rockfill materials

Crushing of grains can greatly influence the strength,dilatancy,and stress-strain relationship of rockfill materials.The critical state line(CSL)in the void ratio versus mean effective stress plane was extended to the breakage critical state plane(BCSP).A state void-ratio-pressure index that incorporated the effect of grain crushing was proposed according to the BCSP.Rowe’s stress-dilatancy equation was modified by adding the breakage voidratio-pressure index,which was also incorporated into the formulations of the bounding stress ratio and plastic modulus.A BCSP-based bounding surface plasticity model was proposed to describe the state-dependent stressstrain behaviors and the evolution of grain crushing during shearing process of rockfill materials,and was shown to sufficiently capture the breakage phenomenon.

Low-Rate DoS Attack Flows Filtering Based on Frequency Spectral Analysis

In frequency domain,the power spectrum of Low-rate denial of service(LDoS) attacks is totally spread into the spectrum of normal traffic.It is a challenging task to detect and filter LDoS attack flows from the normal traffic.Based on the analysis of LDoS attack flows and legitimate TCP traffic in time and frequency domains,the periodicity of the TCP traffic and LDoS attack flows is explored to facilitate the research of network traffic processing.Hence,an approach of LDoS attack flow filtering based on frequency spectrum analysis is proposed.In this approach,the TCP traffic and LDoS attack flows are transformed from the time domain into the frequency domain.Then the round-trip time(RTT) is estimated by using frequency domain search method.Analysis of amplitude spectrum shows that TCP traffic energy is mainly concentrated on the points of n/RTT.Therefore,a comb filter using infinite impulse response(IIR) filter is designed to filter out the LDoS attack flows in frequency domain,while most legitimate TCP traffic energy at the points of n/RTT are pass through.Experimental results show that the maximum pass rate for legitimate TCP traffic reaches 92.55%,while the maximum filtration rate of LDoS attack flows reaches 81.36%.The proposed approach can effectively filter the LDoS attack flows while less impact on the legitimate TCP traffic.

An efficient probabilistic design approach for tunnel face stability by inverse reliability analysis

In order to maintain the safety of underground constructions that significantly involve geo-material uncertainties,this paper delivers a new computation framework for conducting reliability-based design(RBD)of shallow tunnel face stability,utilizing a simplified inverse first-order reliability method(FORM).The limit state functions defining tunnel face stability are established for both collapse and blow-out modes of the tunnel face failure,respectively,and the deterministic results of the tunnel face support pressure are obtained through three-dimensional finite element limit analysis(FELA).Because the inverse reliability method can directly capture the design support pressure according to prescribed target reliability index,the computational cost for probabilistic design of tunnel face stability is greatly reduced.By comparison with Monte Carlo simulation results,the accuracy and feasibility of the proposed method are verified.Further,this study presents a series of reliability-based design charts for vividly understanding the limit support pressure on tunnel face in both cohesionless(sandy)soil and cohesive soil stratums,and their optimal support pressure ranges are highlighted.The results show that in the case of sandy soil stratum,the blowout failure of tunnel face is extremely unlikely,whereas the collapse is the only possible failure mode.The parametric study of various geotechnical uncertainties also reveals that ignoring the potential correlation between soil shear strength parameters will lead to over-designed support pressure,and the coefficient of variation of internal friction angle has a greater influence on the tunnel face failure probability than that of the cohesion.

Propagation of positive, negative, and recoil leaders in upward lightning flashes

Leader propagation is a fundamental issue in lightning physics. The propagation characteristics of positive leaders and negative leaders are summarized and compared based on data from high-speed camera and electromagnetic field in rocket-triggered lightning and tower-initiated lightning discharges; available channel base current data recorded in rocket-triggered lightning are also used. The negative leaders propagate in a stepped fashion accompanied by many branches. The stems ahead of the negative leader tip determine the manner and direction of the leader propagation, and even the branching and winding of the lightning channel. The impulsive current, electromagnetic field, and related optical images suggest that the positive leader may develop in a step-like fashion at its initial stage of triggered lightning. However, the stepping processes of the positive leader are obviously different from those of the negative leader. Tower-initiated lightning revealed that the most conspicuous characteristics of the stepwise positive leader involve the intermittent brush-like corona zone in front of the leader tip and the luminosity enhancement of the channel behind the tip. In rockettriggered lightning flashes, the charge transferred during an individual step for the negative leader was nearly an order greater than for the positive counterpart. The successive streamers ahead of the leader tip are essential for both negative and positive leader propagation, and the stems could be formed from one or more streamers in the previous negative streamer zone with the main leader channel dim. High-resolution observation of tower lightning also revealed a new type of bidirectional recoil leader, with polarity contrary to the traditional one, traversing in negative channels associated with tower-initiated and rocket-triggered lightning.

TESLA-Based Authentication for BeiDou Civil Navigation Message

Due to the civil BeiDou navigation system is open,unauthenticated,and non-encrypted,civilian BeiDou navigation signals may have great security loopholes during transmission or reception.The main security loophole here is spoofing attacks.Spoofing attacks make the positioning or timing results of BeiDou civilian receivers wrong.Such errors may cause a series of security problems,which lays a serious hidden danger for Bei-Dou satellite information security.This article proposes an anti-spoofing method for BeiDou navigation system based on the combination of SM commercial cryptographic algorithm and Timed Efficient Stream Loss-tolerant Authentication(TESLA)for spoofing attacks.In this solution,we use the SM3 algorithm to generate a TESLA key chain with time information,and then use the key in the key chain to generate the message authentication code for the BeiDou D2 navigation message.The message authentication code is inserted into a reserved bit of the D2 navigation message.In addition,this solution uses the SM2 algorithm to protect and encrypt time information in the TESLA key chain to prevent key replay attacks in TESLA.The experimental results tested on the experimental platform built in this paper show that this scheme reduces the possibility of the BeiDou navigation system being deceived and enhances the safety of the BeiDou navigation system.

The detection method of low-rate DoS attack based on multi-feature fusion

As a new type of Denial of Service(DoS)attacks,the Low-rate Denial of Service(LDoS)attacks make the traditional method of detecting Distributed Denial of Service Attack(DDoS)attacks useless due to the characteristics of a low average rate and concealment.With features extracted from the network traffic,a new detection approach based on multi-feature fusion is proposed to solve the problem in this paper.An attack feature set containing the Acknowledge character(ACK)sequence number,the packet size,and the queue length is used to classify normal and LDoS attack traffics.Each feature is digitalized and preprocessed to fit the input of the K-Nearest Neighbor(KNN)classifier separately,and to obtain the decision contour matrix.Then a posteriori probability in the matrix is fused,and the fusion decision index D is used as the basis of detecting the LDoS attacks.Experiments proved that the detection rate of the multi-feature fusion algorithm is higher than those of the single-based detection method and other algorithms.

C@Ag/TiO₂: A Highly Efficient and Stable Photocatalyst Active under Visible Light

In this paper, preparation and characterization of C@Ag/TiO2 nanospheres compound photocatalysts was reported. C@Ag nanosphere was firstly synthesized via hydrothermal reaction, and followed by a sol-gel process to obtain the functionalized C@Ag/TiO2 nanosphere which has highly efficient visible light catalytic ability towards methyl orange (MO). The morphology of the obtained compound was characterized by scanning electron microscopy (SEM) and transmission electron microscopy (TEM) technologies. From which we can see that the as-prepared samples show a spherical structure with a diameter of approximately 200 nm, and the silver particle in core was about 10 nm. The catalytic ability of the synthesized photocatalysts under visible light irradiation shows that C@Ag/TiO2 possesses higher photocatalytic activity towards MO degradation than that of N-P25 (TiO2). Furthermore, the C@Ag/TiO2 photocatalysts exhibited excellent reusability with almost no change after five runs. Finally, the possible photocatalytic mechanism of catalyst under visible light was discussion and proposed.

Pulse-Pair Interference Automatic Detection and Mitigation for L-Band Aeronautical Communication System

Pulse-pairs(PP) generated by distance measuring equipment(DME) cause severe interference to the L-band digital aeronautical communication systems.Unlike previous works that mainly improved receiver structure for mitigating the DME interference, this paper proposes a novel and practical time domain PP mitigation method without changing the existing receiver structure.Our method is composed of three parts and utilizes a specific property, i.e., a relatively fixed waveform of DME PP. First, the complex-valued waveform of PP is automatically detected through an iterative weighted average method. Then, on the basis of the detected PP waveform,each PP is reconstructed according to its amplitude, position, and initial phase, which are estimated through a sparse representation algorithm. Finally, the reconstructed PPs are subtracted from the contaminated signal. Numerical experiments show that compared with recently published methods the bit error rate obtained by our method is approximately 5 dB better, while the complexity is maintained at the same level.

Surface tension of single suspended aerosol microdroplets

The surface tension of troposphere aerosols can significantly influence their atmospheric processes and key properties, particularly on the morphology, the phase transition, the activation as cloud condensation nuclei, and the gas-particle partitioning. However, directly measuring the surface tension of single ambient aerosol is quite challenging, due to the limitations of their picolitre volumes and thermal motion. Here, we developed a dual laser tweezers Raman spectroscopy(DLT-RS) system to directly sense the surface tension of single airborne microdroplets(PM10particles). A pair of aerosol droplets were trapped and driven to coalesce by the laser tweezers. Meanwhile, the backscattering light intensity and brightfield images during the coalescence process were recorded to characterize the aerosol surface tension. A remarkable advantage of directly sensing aerosol surface tension is that the solutes in aerosols are often supersaturated, which is common in atmospheric aerosols but almost unavailable in bulk solutions.We experimentally measured the surface tension of aerosols composed of nitrates or oxalic acid/nitrate mixture. Besides, the variation of surface tension during aerosol aging process was also explored, which brings possible implications on the surface evolution of actual ambient aerosol during their atmospheric lifetime.

Bone metastasis is a late-onset and unfavorable event in survivors of gastric cancer after radical gastrectomy:Results from a clinical observational cohort

Background The timing and incidence of recurrent bone metastasis(BM)after radical gastrectomy in patients with gastric cancer(GC)as well as the survival of these patients were not fully understood.The aim of this study was to analyze the data of an observational GC cohort and identify patients who underwent curative gastrectomy and had recurrent BM to describe and clarify the pattern and profile of BM evolution after surgery.Methods Data were retrieved from a hospital-based GC cohort,and patients who underwent upfront radical gastrectomy were selected.The time points of specific organ metastatic events were recorded,and the person-year incidence rate of metastatic events was calculated.The latency period of BM events after gastrectomy was measured and compared with that of the other two most common metastatic events,liver metastasis(LM)and distant lymph node metastasis(LNM),using analysis of variance.Propensity score matching and subgroup analysis were used for sensitivity analysis.Results A total of 1324 GC cases underwent radical gastrectomy between January 2011 and December 2021.Of these,67 BM,218 LM,and 248 LNM occurred before the last follow-up.The incidence of BM events was 1.7/100 person-years,which was approximately 3-fold lower than that of LM and distant LNM events(5.5 and 6.3 per 100 person-years,respectively).BM events had a significantly longer latency(median time,16.5 months)than LM and LNM events(11.1 and 12.0 months,respectively).Recurrent BM led to a worse prognosis(median survival,4.5 months)than those of LM and LNM events(median survival,7.7 and 7.1 months,respectively).However,no difference in overall survival after gastrectomy was observed among the groups.Conclusions Compared with other common metastatic events,BM in GC after gastrectomy is a late-onset event indicating poor survival.

Effects of heterogeneous reaction with NO_(2) on ice nucleation activities of feldspar and Arizona Test Dust

Mineral dust is an important type of ice nucleating particles in the troposphere;however,the effects of heterogeneous reactions on ice nucleation(IN)activities of mineral dust remain to be elucidated.A droplet-freezing apparatus(Guangzhou Institute of Geochemistry Ice Nucleation Apparatus,GIGINA)was developed in thiswork to measure IN activities of atmospheric particles in the immersion freezingmode,and its performancewas validated by a series of experimental characterizations.This apparatus was then employed to measure IN activities of feldspar and Arizona Test Dust(ATD)particles before and after heterogeneous reaction with NO_(2)(10±0.5 ppmv)at 40%relative humidity.The surface coverage of nitrate,θ(NO_(3)^(−)),increased to 3.1±0.2 for feldspar after reaction with NO_(2) for 6 hr,and meanwhile the active site density per unit surface area(ns)at-20℃ was reduced from 92±5 to<1.0 cm^(−2) by about two orders of magnitude;however,no changes in nitrate content or IN activities were observed for further increase in reaction time(up to 24 hr).Both nitrate content and IN activities changed continuously with reaction time(up to 24 hr)for ATD particles;after reaction with NO_(2) for 24 hr,θ(NO_(3)^(−))increased to 1.4±0.1 and ns at-20℃ was reduced from 20±4 to 9.7±1.9 cm^(−2) by a factor of∼2.Our work suggests that heterogeneous reaction with NO_(2),an abundant reactive nitrogen species in the troposphere,may significantly reduce IN activities of mineral dust in the immersion freezing mode.

Measurement of atmospheric nanoparticles:Bridging the gap between gas-phase molecules and larger particles

Atmospheric nanoparticles are crucial components contributing to fine particulate matter(PM_(2.5)),and therefore have significant effects on visibility,climate,and human health.Due to the unique role of atmospheric nanoparticles during the evolution process from gas-phase molecules to larger particles,a number of sophisticated experimental techniques have been developed and employed for online monitoring and characterization of the physical and chemical properties of atmospheric nanoparticles,helping us to better understand the formation and growth of new particles.In this paper,we firstly review these state-of-the-art techniques for investigating the formation and growth of atmospheric nanoparticles(e.g.,the gas-phase precursor species,molecular clusters,physicochemical properties,and chemical composition).Secondly,we present findings from recent field studies on the formation and growth of atmospheric nanoparticles,utilizing several advanced techniques.Further-more,perspectives are proposed for technique development and improvements in measuring atmospheric nanoparticles.

Output Prediction of Helical Microfiber Temperature Sensors in Cycling Measurement by Deep Learning

The inconsistent response curve of delicate micro/nanofiber(MNF)sensors during cycling measurement is one of the main factors which greatly limit their practical application.In this paper,we proposed a temperature sensor based on the copper rod-supported helical microfiber(HMF).The HMF sensors exhibited different light intensity-temperature response relationships in single-cycle measurements.Two neural networks,the deep belief network(DBN)and the backpropagation neural network(BPNN),were employed respectively to predict the temperature of the HMF sensor in different sensing processes.The input variables of the network were the sensor geometric parameters(the microfiber diameter,wrapped length,coiled turns,and helical angle)and the output optical intensity under different working processes.The root mean square error(RMSE)and Pearson correlation coefficient(R)were used to evaluate the predictive ability of the networks.The DBN with two restricted Boltzmann machines(RBMs)provided the best temperature prediction results(RMSE and R of the heating process are 0.9705℃and 0.9969,while the values of RMSE and R of the cooling process are 0.7866℃and 0.9977,respectively).The prediction results obtained by the optimal BPNN(five hidden layers,10 neurons in each layer,RMSE=1.1266℃,R=0.9957)were slightly inferior to those obtained by the DBN.The neural network could accurately and reliably predict the response of the HMF sensor in cycling operation,which provided the possibility for the flexible application of the complex MNF sensor in a wide sensing range.

Significant effects of transport on nanoparticles during new particle formation events in the atmosphere of Beijing

The mechanisms of new particle formation(NPF)events that occurred under high aerosol loadings(“polluted”NPF)in the atmosphere have been unclear,which has inhibited the precision of particlepollution control.To deepen the understanding of how the“polluted”NPF events occur,a one-monthcomprehensive measurement was conducted in the atmosphere of Beijing during the summer of2016.The“clean”NPF events(frequency=22%)(condensation sink,CS<0.015 s^(-1))were found to becaused by local nucleation and growth.The“polluted”NPF events(frequency=28%)(CS>0.015 s^(-1))were influenced by both local nucleation-growth and regional transport,and the contributions from thetwo factors to 6e25 nm particle number concentration were 60%and 40%,respectively.This studyemphasized the importance of the transport for nanoparticles in relatively polluted atmospheres,and forthat the regional joint particle pollution control would be an essential policy.

我国城市大气PM_(2.5)与O_(3)浓度相关性的时空特征分析

近些年,我国大气PM_(2.5)的质量浓度显著降低,O_(3)污染加剧.为了厘清PM_(2.5)和O_(3)浓度相关性的时空差异,本研究分析了我国城市大气PM_(2.5)浓度与O_(3)日最大8 h滑动平均值(MDA8 O_(3))和大气总氧化剂(O_(x)=O_(3)+NO_(2))浓度之间的相关性.2015年以来,PM_(2.5)与O_(3)双超标天数大幅下降,现阶段双超标情况主要发生在京津冀地区的4~5月.在40°N以南的地区,PM_(2.5)与O_(3)浓度的相关性呈现显著的“南高北低、夏高冬低”的时空分布规律.较强的正相关关系出现在中纬度京津冀地区的夏季以及低纬度的珠江三角洲地区,表明这些区域O_(3)和PM_(2.5)的浓度具有相同的变化趋势;而在京津冀地区的冬季,由于PM_(2.5)中一次组分占比增高以及较弱的O_(3)光化学生成,O_(3)和PM_(2.5)浓度具有相反的变化趋势.不同于PM_(2.5)与MDA8 O_(3)之间的关系,PM_(2.5)与O_(x)在不同季节均表现出较好的正相关性,表明我国大气的强氧化性驱动了PM_(2.5)中二次组分的生成.在O_(3)超标的情况下(MDA8 O_(3)>160μg/m^(3)),PM_(2.5)和O_(3)浓度的相关性与PM_(2.5)浓度有关,当PM_(2.5)浓度低于50μg/m^(3)时,O_(3)与PM_(2.5)浓度具有较好的正相关性,呈现同步变化趋势;当PM_(2.5)浓度进一步增加时,二者浓度具有相反的变化趋势,说明更高浓度的PM_(2.5)可能会抑制O_(3)生成.