Due to space constraints in mountainous areas,twin tunnels are sometimes constructed very close to each other or even overlap.This proximity challenges the structural stability of tunnels built with the drill-and-blas...Due to space constraints in mountainous areas,twin tunnels are sometimes constructed very close to each other or even overlap.This proximity challenges the structural stability of tunnels built with the drill-and-blast method,as the short propagation distance amplifies blasting vibrations.A case of blasting damage is reported in this paper,where concrete cracks crossed construction joints in the twin-arch lining.To identify the causes of these cracks and develop effective vibration mitigation measures,field monitoring and numerical analysis were conducted.Specifically,a restart method was used to simulate the second peak particle velocity(PPV)of MS3 delays occurring 50 ms after the MS1 delays.The study found that the dynamic tensile stress in the tunnel induced by the blast wave has a linear relationship with the of the product of the concrete wave impedance and the PPV.A blast vibration velocity exceeding 23.3 cm/s resulted in tensile stress in the lining surpassing the ultimate tensile strength of C30 concrete,leading to tensile cracking on the blast-facing arch of the constructed tunnel.To control excessive vi-bration velocity,a mitigation trench was implemented to reduce blast wave impact.The trench,approximately 15 m in length,50 cm in width,and 450 cm in height,effectively lowered vibration ve-locities,achieving an average reduction rate of 52%according to numerical analysis.A key innovation of this study is the on-site implementation and validation of the trench's effectiveness in mitigating vi-brations.A feasible trench construction configuration was proposed to overcome the limitations of a single trench in fully controlling vibrations.To further enhance protection,zoned blasting and an auxiliary rock pillar,80 cm in width,were incorporated to reinforce the mid-wall.This study introduces novel strategies for vibration protection in tunnel blasting,offering innovative solutions to address blasting-induced vibrations and effectively minimize their impact,thereby enhancing safety and struc-tural stability.展开更多
During the development of the nervous system,there is an overproduction of neurons and synapses.Hebbian competition between neighboring nerve endings and synapses performing different activity levels leads to their el...During the development of the nervous system,there is an overproduction of neurons and synapses.Hebbian competition between neighboring nerve endings and synapses performing different activity levels leads to their elimination or strengthening.We have extensively studied the involvement of the brain-derived neurotrophic factor-Tropomyosin-related kinase B receptor neurotrophic retrograde pathway,at the neuromuscular junction,in the axonal development and synapse elimination process versus the synapse consolidation.The purpose of this review is to describe the neurotrophic influence on developmental synapse elimination,in relation to other molecular pathways that we and others have found to regulate this process.In particular,we summarize our published results based on transmitter release analysis and axonal counts to show the different involvement of the presynaptic acetylcholine muscarinic autoreceptors,coupled to downstream serine-threonine protein kinases A and C(PKA and PKC)and voltage-gated calcium channels,at different nerve endings in developmental competition.The dynamic changes that occur simultaneously in several nerve terminals and synapses converge across a postsynaptic site,influence each other,and require careful studies to individualize the mechanisms of specific endings.We describe an activity-dependent balance(related to the extent of transmitter release)between the presynaptic muscarinic subtypes and the neurotrophin-mediated TrkB/p75NTR pathways that can influence the timing and fate of the competitive interactions between the different axon terminals.The downstream displacement of the PKA/PKC activity ratio to lower values,both in competing nerve terminals and at postsynaptic sites,plays a relevant role in controlling the elimination of supernumerary synapses.Finally,calcium entry through L-and P/Q-subtypes of voltage-gated calcium channels(both channels are present,together with the N-type channel in developing nerve terminals)contributes to reduce transmitter release and promote withdrawal of the most unfavorable nerve terminals during elimination(the weakest in acetylcholine release and those that have already become silent).The main findings contribute to a better understanding of punishment-rewarding interactions between nerve endings during development.Identifying the molecular targets and signaling pathways that allow synapse consolidation or withdrawal of synapses in different situations is important for potential therapies in neurodegenerative diseases.展开更多
Introduction Progress toward the global elimination of cervical cancer as a public health concern remains slow and highly uneven across countries.High-income nations such as Australia and FinlandDboth of which have ac...Introduction Progress toward the global elimination of cervical cancer as a public health concern remains slow and highly uneven across countries.High-income nations such as Australia and FinlandDboth of which have achieved high human papillomavirus(HPV)vaccination coverage and implemented quality-assured cervical cancer screening programs-have successfully decreased the incidence rates to below 8 cases per 100,000 women~1.These countries are on track to reach the elimination threshold of fewer than 4 cases per 100,000 women within the next few years,as defined by the World Health Organization(WHO).展开更多
As the density of wireless networks increases globally, the vulnerability of overlapped dense wireless communications to interference by hidden nodes and denial-of-service (DoS) attacks is becoming more apparent. Ther...As the density of wireless networks increases globally, the vulnerability of overlapped dense wireless communications to interference by hidden nodes and denial-of-service (DoS) attacks is becoming more apparent. There exists a gap in research on the detection and response to attacks on Medium Access Control (MAC) mechanisms themselves, which would lead to service outages between nodes. Classifying exploitation and deceptive jamming attacks on control mechanisms is particularly challengingdue to their resemblance to normal heavy communication patterns. Accordingly, this paper proposes a machine learning-based selective attack mitigation model that detects DoS attacks on wireless networks by monitoring packet log data. Based on the type of detected attack, it implements effective corresponding mitigation techniques to restore performance to nodes whose availability has been compromised. Experimental results reveal that the accuracy of the proposed model is 14% higher than that of a baseline anomaly detection model. Further, the appropriate mitigation techniques selected by the proposed system based on the attack type improve the average throughput by more than 440% compared to the case without a response.展开更多
Nature-based solutions(NBS)involve the sustainable maintenance,management,and restoration of natural or modified ecosystems.Flooding is a major problem in Phnom Penh,Cambodia,and has significant social and economic ra...Nature-based solutions(NBS)involve the sustainable maintenance,management,and restoration of natural or modified ecosystems.Flooding is a major problem in Phnom Penh,Cambodia,and has significant social and economic ramifications.This study tries to suggest creative solutions that support human welfare and biodiversity while simultaneously resolving social problems by adopting NBS.An online survey using convenience and snowball sampling was conducted to assess the openness of Phnom Penh residents to adopting NBS for flood mitigation in their homes or buildings.The survey investigated perceptions of NBS effectiveness based on previous knowledge and flood risk perception.Results revealed a strong correlation between perceived efficacy and willingness to adopt NBS.Specifically,flood risk perception and prior knowledge significantly influenced the perceived effectiveness of NBS.Key findings indicate that high installation and maintenance costs,lack of awareness,limited space,cultural factors,and perceived ineffectiveness are primary barriers to NBS adoption.Additionally,specific regional factors contribute to reluctance in certain areas of Phnom Penh.To overcome these barriers,the study recommends that the Cambodian government and other stakeholders invest in public education campaigns to raise awareness about the benefits of NBS.Financial incentives and subsidies should be provided to reduce the economic burden on residents.Furthermore,integrating NBS into urban planning and infrastructure development is crucial to enhance community resilience against floods.展开更多
Public participation is crucial in mitigating disasters.Stemming from the ongoing debate on benefit-and risk-driven approaches to landslide mitigation,this study seeks to uncover the factors and underlying mechanisms ...Public participation is crucial in mitigating disasters.Stemming from the ongoing debate on benefit-and risk-driven approaches to landslide mitigation,this study seeks to uncover the factors and underlying mechanisms that affect farmers'willingness to participate in landslide prevention and mitigation(WPLPM).Conducted in Heifangtai,Gansu Province,China,renowned as the"landslide natural laboratory",this research employs multiple linear regression analysis on data from 399 questionnaires to pinpoint the key determinants of farmers'WPLPM.The findings reveal:(1)the"risk perception paradox"exists—farmers have high-risk perception but low WPLPM;(2)the impact of risk perception on WPLPM is tempered by self-efficacy related to fund,learning ability,and operation ability,offering an insight into the"risk perception paradox";and(3)There are significant positive influences of farmers'benefit perception,social network,and perceived responsibility on their WPLPM.Based on these insights,the study offers targeted policy recommendations.展开更多
Over the past few years,Malware attacks have become more and more widespread,posing threats to digital assets throughout the world.Although numerous methods have been developed to detect malicious attacks,these malwar...Over the past few years,Malware attacks have become more and more widespread,posing threats to digital assets throughout the world.Although numerous methods have been developed to detect malicious attacks,these malware detection techniques need to be more efficient in detecting new and progressively sophisticated variants of malware.Therefore,the development of more advanced and accurate techniques is necessary for malware detection.This paper introduces a comprehensive Dual-Channel Attention Deep Bidirectional Long Short-Term Memory(DCADBiLSTM)model for malware detection and riskmitigation.The Dual Channel Attention(DCA)mechanism improves themodel’s capability to concentrate on the features that aremost appropriate in the input data,which reduces the false favourable rates.The Bidirectional Long,Short-Term Memory framework helps capture crucial interdependence from past and future circumstances,which is essential for enhancing the model’s understanding of malware behaviour.As soon as malware is detected,the risk mitigation phase is implemented,which evaluates the severity of each threat and helps mitigate threats earlier.The outcomes of the method demonstrate better accuracy of 98.96%,which outperforms traditional models.It indicates the method detects and mitigates several kinds of malware threats,thereby providing a proactive defence mechanism against the emerging challenges in cybersecurity.展开更多
Internal multiples are commonly present in seismic data due to variations in velocity or density of subsurface media.They can reduce the signal-to-noise ratio of seismic data and degrade the quality of the image.With ...Internal multiples are commonly present in seismic data due to variations in velocity or density of subsurface media.They can reduce the signal-to-noise ratio of seismic data and degrade the quality of the image.With the development of seismic exploration into deep and ultradeep events,especially those from complex targets in the western region of China,the internal multiple eliminations become increasingly challenging.Currently,three-dimensional(3D)seismic data are primarily used for oil and gas target recognition and drilling.Effectively eliminating internal multiples in 3D seismic data of complex structures and mitigating their adverse effects is crucial for enhancing the success rate of drilling.In this study,we propose an internal multiple prediction algorithm for 3D seismic data in complex structures using the Marchenko autofocusing theory.This method can predict the accurate internal multiples of time difference without an accurate velocity model and the implementation process mainly consists of several steps.Firstly,simulating direct waves with a 3D macroscopic velocity model.Secondly,using direct waves and 3D full seismic acquisition records to obtain the upgoing and down-going Green's functions between the virtual source point and surface.Thirdly,constructing internal multiples of the relevant layers by upgoing and downgoing Green's functions.Finally,utilizing the adaptive matching subtraction method to remove predicted internal multiples from the original data to obtain seismic records without multiples.Compared with the two-dimensional(2D)Marchenko algo-rithm,the performance of the 3D Marchenko algorithm for internal multiple prediction has been significantly enhanced,resulting in higher computational accuracy.Numerical simulation test results indicate that our proposed method can effectively eliminate internal multiples in 3D seismic data,thereby exhibiting important theoretical and industrial application value.展开更多
This research investigates the effectiveness of climate-related development aid in Indonesia’s climate mitigation.Specific objectives include assessing the contribution of official development assistance(ODA)to reduc...This research investigates the effectiveness of climate-related development aid in Indonesia’s climate mitigation.Specific objectives include assessing the contribution of official development assistance(ODA)to reducing CO_(2) emissions and evaluating the implementation of the Busan Principles of aid effectiveness to achieve Indonesia’s mitigation priorities and targets.We utilize a new primary dataset based on interviews with the most knowledgeable stakeholders of ODA on climate change mitigation.Additionally,we use secondary data from the annual Rio Marker and the Common Reporting Standard data of the Organization for Economic Co-operation and Development.The results show a significant correlation between climate-related development aid and CO_(2) emission reduction in Indonesia.Additionally,the implementation of the Busan Principles enhances aid management by fostering project ownership and increasing the involvement of civil society and private sector.The study has implications for devising an effective climate change mitigation strategy for Indonesia.It is suggested that the government of Indonesia exercise greater flexibility and dynamism in engaging with development partners.展开更多
The global supply chain turbulence has increased the difficulty of protecting foreign well-known trademarks.Although there are many studies on cross-border trademark rights protection in academia,there is relatively l...The global supply chain turbulence has increased the difficulty of protecting foreign well-known trademarks.Although there are many studies on cross-border trademark rights protection in academia,there is relatively little research on its risk mitigation effectiveness in the context of supply chain fluctuations.Based on case studies of commercial law and data statistics,the study explores the relationship between protection efficiency and market response through legal applicability.Due to the long litigation cycle and uneven law enforcement,there are differences in market regulation,weakening the protection of well-known trademarks and exacerbating supply chain uncertainty.Strengthening international legal framework cooperation and promoting law enforcement linkage can enhance protection effectiveness.In theory,enriching the theory of cross-border trademark protection and expanding research on brand rights protection in the context of global supply chains.In practice,it helps enterprises adjust their trademark layout,avoid legal risks,and improve market competitiveness.Due to the complexity of the legal environment and limitations in data acquisition,future research will strengthen data analysis,promote international cooperation in intelligent supervision,and build a more efficient cross-border well-known trademark protection mechanism.展开更多
Large-scale deep-seated landslides pose a significant threat to human life and infrastructure.Therefore,closely monitoring these landslides is crucial for assessing and mitigating their associated risks.In this paper,...Large-scale deep-seated landslides pose a significant threat to human life and infrastructure.Therefore,closely monitoring these landslides is crucial for assessing and mitigating their associated risks.In this paper,the authors introduce the So Lo Mon framework,a comprehensive monitoring system developed for three large-scale landslides in the Autonomous Province of Bolzano,Italy.A web-based platform integrates various monitoring data(GNSS,topographic data,in-place inclinometer),providing a user-friendly interface for visualizing and analyzing the collected data.This facilitates the identification of trends and patterns in landslide behaviour,enabling the triggering of warnings and the implementation of appropriate mitigation measures.The So Lo Mon platform has proven to be an invaluable tool for managing the risks associated with large-scale landslides through non-structural measures and driving countermeasure works design.It serves as a centralized data repository,offering visualization and analysis tools.This information empowers decisionmakers to make informed choices regarding risk mitigation,ultimately ensuring the safety of communities and infrastructures.展开更多
Reducing greenhouse gas(GHG)emissions to address climate change is a global consensus,and municipal wastewater treatment plants(MWWTPs)should lead the way in low-carbon sustainable development.However,achieving efflue...Reducing greenhouse gas(GHG)emissions to address climate change is a global consensus,and municipal wastewater treatment plants(MWWTPs)should lead the way in low-carbon sustainable development.However,achieving effluent discharge standards often requires considerable energy and chemical consumption during operation,resulting in significant carbon footprints.In this study,GHG emissions are systematically accounted for,and the driving factors of carbon footprint growth in China’s MWWTPs are explored.In 2020,a total of 41.9 million tonnes(Mt)of carbon dioxide equivalent(CO_(2)-eq)were released by the sector,with nearly two-thirds being indirect emissions resulting from energy and material usage.The intensity of electricity,carbon source,and phosphorus removing agent consumption increasingly influence carbon footprint growth over time.Through statistical inference,benchmarks for electricity and chemical consumption intensity are established across all MWWTPs under various operational conditions,and the potential for mitigation through more efficient energy and material utilization is calculated.The results suggest that many MWWTPs offer significant opportunities for emission reduction.Consequently,empirical decarbonization measures,including intelligent device control,optimization of aeration equipment,energy recovery initiatives,and other enhancements to improve operational and carbon efficiency,are recommended.展开更多
EHL-2 is a compact,high-field spherical tokamak designed to explore the potential of an advanced p-11B nuclear fusion reactor.Due to its high plasma current and thermal energy,it is crucial to mitigate the impact asso...EHL-2 is a compact,high-field spherical tokamak designed to explore the potential of an advanced p-11B nuclear fusion reactor.Due to its high plasma current and thermal energy,it is crucial to mitigate the impact associated with disruptions to ensure the safe operation of EHL-2.This paper evaluates the performance requirements of the disruption prediction system on EHL-2,with a particular focus on applying generalizable knowledge transfer from existing devices to future ones.Furthermore,the key characteristics of disruption mitigation strategies are analyzed,and their overall mitigation performance on EHL-2 is assessed.This insight provides valuable guidance for optimizing the engineering design of EHL-2 and identifying its optimal operational regime.展开更多
In May 2018,the Director-General of the World Health Organization(WHO)called for global action to eliminate cervical cancer~1.This call marked the beginning of an ambitious international effort to scale up 3 key strat...In May 2018,the Director-General of the World Health Organization(WHO)called for global action to eliminate cervical cancer~1.This call marked the beginning of an ambitious international effort to scale up 3 key strategies:human papillomavirus(HPV)vaccination,cervical cancer screening,and treatment of precancerous lesions and cancer.Subsequently,the WHO and its partners developed a global strategy to accelerate the reduction of cervical cancer incidence,with an ultimate goal of achieving elimination within the next century.This Global Strategy represents a formal international commitment and is anchored in the 90-70-90 targets to be achieved by 2030.In parallel,several countries have also set national commitments,such as Sweden's pledge to achieve elimination by 2027 and Australia's target of achieving elimination by 2035.展开更多
China has achieved the poverty reduction goal of the United Nations 2030 Agenda for Sustainable Development 10 years ahead of schedule,contributing significantly to global poverty reduction.Despite extended efforts in...China has achieved the poverty reduction goal of the United Nations 2030 Agenda for Sustainable Development 10 years ahead of schedule,contributing significantly to global poverty reduction.Despite extended efforts in poverty elimination,there is a lack of quantitative studies categorizing and comparing poverty-elimination counties(PECs)based on their processes.This study proposes an innovative framework for analyzing PECs’development paths from the perspective of population-land-industry(PLI).We quantify the PLI matching degree of PECs in China during the critical phase of the battle against poverty through a multivariate matching model,classify PECs via K-means clustering according to the consistency in PLI matching degree evolution,and summarize the typical development patterns of PECs.Results indicate that the PLI matching degree of PECs in China increased substantially from 2015 to 2020,particularly in eastern areas,while the western region,including the Qinghai-Xizang Plateau and southwestern Xinjiang,shows untapped potential for improvement.Five types of PECs are identified,with the majority(30.1%)showing sustained moderate PLI matching and a minority(9.6%)experiencing long-term PLI mismatch.Industry is the shortfall of various PECs,and effective strategies to facilitate all types of PECs include the development of emerging businesses and the expansion of secondary and tertiary industries.Additionally,enriching rural labor force and increasing farmland use efficiency are essential for optimal PLI matching and positive interaction,ultimately ensuring poverty elimination and sustainable development.展开更多
The explosive expansion of the Internet of Things(IoT)systems has increased the imperative to have strong and robust solutions to cyber Security,especially to curtail Distributed Denial of Service(DDoS)attacks,which c...The explosive expansion of the Internet of Things(IoT)systems has increased the imperative to have strong and robust solutions to cyber Security,especially to curtail Distributed Denial of Service(DDoS)attacks,which can cripple critical infrastructure.The proposed framework presented in the current paper is a new hybrid scheme that induces deep learning-based traffic classification and blockchain-enabledmitigation tomake intelligent,decentralized,and real-time DDoS countermeasures in an IoT network.The proposed model fuses the extracted deep features with statistical features and trains them by using traditional machine-learning algorithms,which makes them more accurate in detection than statistical features alone,based on the Convolutional Neural Network(CNN)architecture,which can extract deep features.A permissioned blockchain will be included to record the threat cases immutably and automatically execute mitigation measures through smart contracts to provide transparency and resilience.When tested on two test sets,BoT-IoT and IoT-23,the framework obtains a maximum F1-score at 97.5 percent and only a 1.8 percent false positive rate,which compares favorably to other solutions regarding effectiveness and the amount of time required to respond.Our findings support the feasibility of our method as an extensible and secure paradigm of nextgeneration IoT security,which has constrictive utility in mission-critical or resource-constrained settings.The work is a substantial milestone in autonomous and trustful mitigation against DDoS attacks through intelligent learning and decentralized enforcement.展开更多
The excessive use of artificial intelligence(AI)algorithms has caused the problem of errors in AI algorithms,which has challenged the fairness of decision-making,and has intensified people’s inequality.Therefore,it i...The excessive use of artificial intelligence(AI)algorithms has caused the problem of errors in AI algorithms,which has challenged the fairness of decision-making,and has intensified people’s inequality.Therefore,it is necessary to conduct in-depth research and propose corresponding error detection and error elimination methods.This paper first proposes the root causes and threats of bias in AI algorithms,then summarizes the existing bias detection and error elimination methods,and proposes a bias processing framework in three-level dimensions of data,models,and conclusions,aiming to provide a framework for a comprehensive solution to errors in algorithms.At the same time,it also summarizes the problems and challenges in existing research and makes a prospect for future research trends.It is hoped that it will be helpful for us to build fairer AI.展开更多
Global Navigation Satellite Systems(GNSSs)face significant security threats from spoofing attacks.Typical anti-spoofing methods rely on estimating the delays between spoofing and authentic signals using multicorrelato...Global Navigation Satellite Systems(GNSSs)face significant security threats from spoofing attacks.Typical anti-spoofing methods rely on estimating the delays between spoofing and authentic signals using multicorrelator outputs.However,the accuracy of the delay estimation is limited by the spacing of the correlators.To address this,an innovative anti-spoofing method is introduced,which incorporates distinct coarse and refined stages for more accurate spoofing estimation.By leveraging the coarse delay estimates obtained through maximum likelihood estimation,the proposed method establishes the Windowed Sum of the Relative Delay(WSRD)statistics to detect the presence of spoofing signals.The iterative strategy is then employed to enhance the precision of the delay estimation.To further adapt to variations in the observation noise caused by spoofing intrusions and restore precise position,velocity,and timing solutions,an adaptive extended Kalman filter is proposed.This comprehensive framework offers detection,mitigation,and recovery against spoofing attacks.Experimental validation using datasets from the Texas Spoofing Test Battery(TEXBAT)demonstrates the effectiveness of the proposed anti-spoofing method.With 41 correlators,the method achieves a detection rate exceeding 90%at a false alarm rate of 10-5,with position or time errors below 15 m.Notably,this refined anti-spoofing approach shows robust detection and mitigation capabilities,requiring only a single antenna without the need for additional external sensors.These advancements can significantly contribute to the development of GNSS anti-spoofing measures.展开更多
Internal multiple interference,affecting both seismic data processing and interpretation,has been observed for long time.Although great progress has been achieved in developing a variety of internal-multiple-eliminati...Internal multiple interference,affecting both seismic data processing and interpretation,has been observed for long time.Although great progress has been achieved in developing a variety of internal-multiple-elimination(IME)methods,how to increase accuracy and reduce cost of IME still poses a significant challenge.A new method is proposed to effectively and efficiently eliminate internal multi-ples,along with its application in internal-multiple-eliminated-migration(IMEM),addressing this issue.This method stems from two-way wave equation depth-extrapolation scheme and associated up/down wavefield separation,which can accomplish depth-extrapolation of both up-going and down-going wavefields simultaneously,and complete internal-multiple-elimination processing,adaptively and effi-ciently.The proposed method has several features:(1)input data is same as that for conventional migration:source signature(used for migration only),macro velocity model,and receiver data,without additional requirements for source/receiver sampling;(2)method is efficient,without need of iterative calculations(which are typically needed for most of IME algorithms);and(3)method is cost effective:IME is completed in the same depth-extrapolation scheme of IMEM,without need of a separate pro-cessing and additional cost.Several synthesized data models are used to test the proposed method:one-dimensional model,horizontal layered model,multi-layer model with one curved layer,and SEG/EAGE Salt model.Additionally,we perform a sensitivity analysis of velocity using smoothed models.This analysis reveals that although the accuracy of velocity measurements impacts our proposed method,it significantly reduces internal multiple false imaging compared to traditional RTM techniques.When applied to actual seismic data from a carbonate reservoir zone,our method demonstrates superior clarity in imaging results,even in the presence of high-velocity carbonate formations,outperforming conven-tional migration methods in deep strata.展开更多
基金supported by the Shenzhen Stability Support Plan(Grant No.20231122095154003)National Natural Science Foundation of China(Grant Nos.51978671 and 52378425)Guizhou Provincial Department of Transportation Science and Technology Program(Grant No.2023-122-003)。
文摘Due to space constraints in mountainous areas,twin tunnels are sometimes constructed very close to each other or even overlap.This proximity challenges the structural stability of tunnels built with the drill-and-blast method,as the short propagation distance amplifies blasting vibrations.A case of blasting damage is reported in this paper,where concrete cracks crossed construction joints in the twin-arch lining.To identify the causes of these cracks and develop effective vibration mitigation measures,field monitoring and numerical analysis were conducted.Specifically,a restart method was used to simulate the second peak particle velocity(PPV)of MS3 delays occurring 50 ms after the MS1 delays.The study found that the dynamic tensile stress in the tunnel induced by the blast wave has a linear relationship with the of the product of the concrete wave impedance and the PPV.A blast vibration velocity exceeding 23.3 cm/s resulted in tensile stress in the lining surpassing the ultimate tensile strength of C30 concrete,leading to tensile cracking on the blast-facing arch of the constructed tunnel.To control excessive vi-bration velocity,a mitigation trench was implemented to reduce blast wave impact.The trench,approximately 15 m in length,50 cm in width,and 450 cm in height,effectively lowered vibration ve-locities,achieving an average reduction rate of 52%according to numerical analysis.A key innovation of this study is the on-site implementation and validation of the trench's effectiveness in mitigating vi-brations.A feasible trench construction configuration was proposed to overcome the limitations of a single trench in fully controlling vibrations.To further enhance protection,zoned blasting and an auxiliary rock pillar,80 cm in width,were incorporated to reinforce the mid-wall.This study introduces novel strategies for vibration protection in tunnel blasting,offering innovative solutions to address blasting-induced vibrations and effectively minimize their impact,thereby enhancing safety and struc-tural stability.
基金supported by Catalan Government,Nos.2014SGR344(to JT),2017SGR704(to JT),2021SGR01214(to MAL)MCIN/AEI/10.13039/501100011033/by“ERDF A way of making Europe,”Nos.SAF2015-67143(to JT),PID2019-106332GB-I00(to JT and MAL)and PID2022-141252NB-I00(to MAL).
文摘During the development of the nervous system,there is an overproduction of neurons and synapses.Hebbian competition between neighboring nerve endings and synapses performing different activity levels leads to their elimination or strengthening.We have extensively studied the involvement of the brain-derived neurotrophic factor-Tropomyosin-related kinase B receptor neurotrophic retrograde pathway,at the neuromuscular junction,in the axonal development and synapse elimination process versus the synapse consolidation.The purpose of this review is to describe the neurotrophic influence on developmental synapse elimination,in relation to other molecular pathways that we and others have found to regulate this process.In particular,we summarize our published results based on transmitter release analysis and axonal counts to show the different involvement of the presynaptic acetylcholine muscarinic autoreceptors,coupled to downstream serine-threonine protein kinases A and C(PKA and PKC)and voltage-gated calcium channels,at different nerve endings in developmental competition.The dynamic changes that occur simultaneously in several nerve terminals and synapses converge across a postsynaptic site,influence each other,and require careful studies to individualize the mechanisms of specific endings.We describe an activity-dependent balance(related to the extent of transmitter release)between the presynaptic muscarinic subtypes and the neurotrophin-mediated TrkB/p75NTR pathways that can influence the timing and fate of the competitive interactions between the different axon terminals.The downstream displacement of the PKA/PKC activity ratio to lower values,both in competing nerve terminals and at postsynaptic sites,plays a relevant role in controlling the elimination of supernumerary synapses.Finally,calcium entry through L-and P/Q-subtypes of voltage-gated calcium channels(both channels are present,together with the N-type channel in developing nerve terminals)contributes to reduce transmitter release and promote withdrawal of the most unfavorable nerve terminals during elimination(the weakest in acetylcholine release and those that have already become silent).The main findings contribute to a better understanding of punishment-rewarding interactions between nerve endings during development.Identifying the molecular targets and signaling pathways that allow synapse consolidation or withdrawal of synapses in different situations is important for potential therapies in neurodegenerative diseases.
文摘Introduction Progress toward the global elimination of cervical cancer as a public health concern remains slow and highly uneven across countries.High-income nations such as Australia and FinlandDboth of which have achieved high human papillomavirus(HPV)vaccination coverage and implemented quality-assured cervical cancer screening programs-have successfully decreased the incidence rates to below 8 cases per 100,000 women~1.These countries are on track to reach the elimination threshold of fewer than 4 cases per 100,000 women within the next few years,as defined by the World Health Organization(WHO).
基金supported by the Ministry of Trade,Industry and Energy(MOTIE)under Training Industrial Security Specialist for High-Tech Industry(RS-2024-00415520)supervised by the Korea Institute for Advancement of Technology(KIAT)the Ministry of Science and ICT(MSIT)under the ICT Challenge and Advanced Network of HRD(ICAN)Program(No.IITP-2022-RS-2022-00156310)supervised by the Institute of Information&Communication Technology Planning&Evaluation(IITP).
文摘As the density of wireless networks increases globally, the vulnerability of overlapped dense wireless communications to interference by hidden nodes and denial-of-service (DoS) attacks is becoming more apparent. There exists a gap in research on the detection and response to attacks on Medium Access Control (MAC) mechanisms themselves, which would lead to service outages between nodes. Classifying exploitation and deceptive jamming attacks on control mechanisms is particularly challengingdue to their resemblance to normal heavy communication patterns. Accordingly, this paper proposes a machine learning-based selective attack mitigation model that detects DoS attacks on wireless networks by monitoring packet log data. Based on the type of detected attack, it implements effective corresponding mitigation techniques to restore performance to nodes whose availability has been compromised. Experimental results reveal that the accuracy of the proposed model is 14% higher than that of a baseline anomaly detection model. Further, the appropriate mitigation techniques selected by the proposed system based on the attack type improve the average throughput by more than 440% compared to the case without a response.
文摘Nature-based solutions(NBS)involve the sustainable maintenance,management,and restoration of natural or modified ecosystems.Flooding is a major problem in Phnom Penh,Cambodia,and has significant social and economic ramifications.This study tries to suggest creative solutions that support human welfare and biodiversity while simultaneously resolving social problems by adopting NBS.An online survey using convenience and snowball sampling was conducted to assess the openness of Phnom Penh residents to adopting NBS for flood mitigation in their homes or buildings.The survey investigated perceptions of NBS effectiveness based on previous knowledge and flood risk perception.Results revealed a strong correlation between perceived efficacy and willingness to adopt NBS.Specifically,flood risk perception and prior knowledge significantly influenced the perceived effectiveness of NBS.Key findings indicate that high installation and maintenance costs,lack of awareness,limited space,cultural factors,and perceived ineffectiveness are primary barriers to NBS adoption.Additionally,specific regional factors contribute to reluctance in certain areas of Phnom Penh.To overcome these barriers,the study recommends that the Cambodian government and other stakeholders invest in public education campaigns to raise awareness about the benefits of NBS.Financial incentives and subsidies should be provided to reduce the economic burden on residents.Furthermore,integrating NBS into urban planning and infrastructure development is crucial to enhance community resilience against floods.
基金funded by National Social Science Foundation of China(Grant Number 24&ZD164)。
文摘Public participation is crucial in mitigating disasters.Stemming from the ongoing debate on benefit-and risk-driven approaches to landslide mitigation,this study seeks to uncover the factors and underlying mechanisms that affect farmers'willingness to participate in landslide prevention and mitigation(WPLPM).Conducted in Heifangtai,Gansu Province,China,renowned as the"landslide natural laboratory",this research employs multiple linear regression analysis on data from 399 questionnaires to pinpoint the key determinants of farmers'WPLPM.The findings reveal:(1)the"risk perception paradox"exists—farmers have high-risk perception but low WPLPM;(2)the impact of risk perception on WPLPM is tempered by self-efficacy related to fund,learning ability,and operation ability,offering an insight into the"risk perception paradox";and(3)There are significant positive influences of farmers'benefit perception,social network,and perceived responsibility on their WPLPM.Based on these insights,the study offers targeted policy recommendations.
基金funded by the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah,under grant No.(IPP:421-611-2025).
文摘Over the past few years,Malware attacks have become more and more widespread,posing threats to digital assets throughout the world.Although numerous methods have been developed to detect malicious attacks,these malware detection techniques need to be more efficient in detecting new and progressively sophisticated variants of malware.Therefore,the development of more advanced and accurate techniques is necessary for malware detection.This paper introduces a comprehensive Dual-Channel Attention Deep Bidirectional Long Short-Term Memory(DCADBiLSTM)model for malware detection and riskmitigation.The Dual Channel Attention(DCA)mechanism improves themodel’s capability to concentrate on the features that aremost appropriate in the input data,which reduces the false favourable rates.The Bidirectional Long,Short-Term Memory framework helps capture crucial interdependence from past and future circumstances,which is essential for enhancing the model’s understanding of malware behaviour.As soon as malware is detected,the risk mitigation phase is implemented,which evaluates the severity of each threat and helps mitigate threats earlier.The outcomes of the method demonstrate better accuracy of 98.96%,which outperforms traditional models.It indicates the method detects and mitigates several kinds of malware threats,thereby providing a proactive defence mechanism against the emerging challenges in cybersecurity.
文摘Internal multiples are commonly present in seismic data due to variations in velocity or density of subsurface media.They can reduce the signal-to-noise ratio of seismic data and degrade the quality of the image.With the development of seismic exploration into deep and ultradeep events,especially those from complex targets in the western region of China,the internal multiple eliminations become increasingly challenging.Currently,three-dimensional(3D)seismic data are primarily used for oil and gas target recognition and drilling.Effectively eliminating internal multiples in 3D seismic data of complex structures and mitigating their adverse effects is crucial for enhancing the success rate of drilling.In this study,we propose an internal multiple prediction algorithm for 3D seismic data in complex structures using the Marchenko autofocusing theory.This method can predict the accurate internal multiples of time difference without an accurate velocity model and the implementation process mainly consists of several steps.Firstly,simulating direct waves with a 3D macroscopic velocity model.Secondly,using direct waves and 3D full seismic acquisition records to obtain the upgoing and down-going Green's functions between the virtual source point and surface.Thirdly,constructing internal multiples of the relevant layers by upgoing and downgoing Green's functions.Finally,utilizing the adaptive matching subtraction method to remove predicted internal multiples from the original data to obtain seismic records without multiples.Compared with the two-dimensional(2D)Marchenko algo-rithm,the performance of the 3D Marchenko algorithm for internal multiple prediction has been significantly enhanced,resulting in higher computational accuracy.Numerical simulation test results indicate that our proposed method can effectively eliminate internal multiples in 3D seismic data,thereby exhibiting important theoretical and industrial application value.
文摘This research investigates the effectiveness of climate-related development aid in Indonesia’s climate mitigation.Specific objectives include assessing the contribution of official development assistance(ODA)to reducing CO_(2) emissions and evaluating the implementation of the Busan Principles of aid effectiveness to achieve Indonesia’s mitigation priorities and targets.We utilize a new primary dataset based on interviews with the most knowledgeable stakeholders of ODA on climate change mitigation.Additionally,we use secondary data from the annual Rio Marker and the Common Reporting Standard data of the Organization for Economic Co-operation and Development.The results show a significant correlation between climate-related development aid and CO_(2) emission reduction in Indonesia.Additionally,the implementation of the Busan Principles enhances aid management by fostering project ownership and increasing the involvement of civil society and private sector.The study has implications for devising an effective climate change mitigation strategy for Indonesia.It is suggested that the government of Indonesia exercise greater flexibility and dynamism in engaging with development partners.
文摘The global supply chain turbulence has increased the difficulty of protecting foreign well-known trademarks.Although there are many studies on cross-border trademark rights protection in academia,there is relatively little research on its risk mitigation effectiveness in the context of supply chain fluctuations.Based on case studies of commercial law and data statistics,the study explores the relationship between protection efficiency and market response through legal applicability.Due to the long litigation cycle and uneven law enforcement,there are differences in market regulation,weakening the protection of well-known trademarks and exacerbating supply chain uncertainty.Strengthening international legal framework cooperation and promoting law enforcement linkage can enhance protection effectiveness.In theory,enriching the theory of cross-border trademark protection and expanding research on brand rights protection in the context of global supply chains.In practice,it helps enterprises adjust their trademark layout,avoid legal risks,and improve market competitiveness.Due to the complexity of the legal environment and limitations in data acquisition,future research will strengthen data analysis,promote international cooperation in intelligent supervision,and build a more efficient cross-border well-known trademark protection mechanism.
基金funded by the So Lo Mon project“Monitoraggio a Lungo Termine di Grandi Frane basato su Sistemi Integrati di Sensori e Reti”(Longterm monitoring of large-scale landslides based on integrated systems of sensors and networks),Program EFRE-FESR 2014–2020,Project EFRE-FESR4008 South Tyrol–Person in charge:V.Mair。
文摘Large-scale deep-seated landslides pose a significant threat to human life and infrastructure.Therefore,closely monitoring these landslides is crucial for assessing and mitigating their associated risks.In this paper,the authors introduce the So Lo Mon framework,a comprehensive monitoring system developed for three large-scale landslides in the Autonomous Province of Bolzano,Italy.A web-based platform integrates various monitoring data(GNSS,topographic data,in-place inclinometer),providing a user-friendly interface for visualizing and analyzing the collected data.This facilitates the identification of trends and patterns in landslide behaviour,enabling the triggering of warnings and the implementation of appropriate mitigation measures.The So Lo Mon platform has proven to be an invaluable tool for managing the risks associated with large-scale landslides through non-structural measures and driving countermeasure works design.It serves as a centralized data repository,offering visualization and analysis tools.This information empowers decisionmakers to make informed choices regarding risk mitigation,ultimately ensuring the safety of communities and infrastructures.
基金supported by the National Natural Science Foundation of China(52200228 and 72022004)the National Key Research and Development Program of China(2021YFC3200205 and 2022YFC3203704).
文摘Reducing greenhouse gas(GHG)emissions to address climate change is a global consensus,and municipal wastewater treatment plants(MWWTPs)should lead the way in low-carbon sustainable development.However,achieving effluent discharge standards often requires considerable energy and chemical consumption during operation,resulting in significant carbon footprints.In this study,GHG emissions are systematically accounted for,and the driving factors of carbon footprint growth in China’s MWWTPs are explored.In 2020,a total of 41.9 million tonnes(Mt)of carbon dioxide equivalent(CO_(2)-eq)were released by the sector,with nearly two-thirds being indirect emissions resulting from energy and material usage.The intensity of electricity,carbon source,and phosphorus removing agent consumption increasingly influence carbon footprint growth over time.Through statistical inference,benchmarks for electricity and chemical consumption intensity are established across all MWWTPs under various operational conditions,and the potential for mitigation through more efficient energy and material utilization is calculated.The results suggest that many MWWTPs offer significant opportunities for emission reduction.Consequently,empirical decarbonization measures,including intelligent device control,optimization of aeration equipment,energy recovery initiatives,and other enhancements to improve operational and carbon efficiency,are recommended.
基金supported by the ENN Group,the ENN Energy Research Institute and National Natural Science Foundation of China(No.12205122).
文摘EHL-2 is a compact,high-field spherical tokamak designed to explore the potential of an advanced p-11B nuclear fusion reactor.Due to its high plasma current and thermal energy,it is crucial to mitigate the impact associated with disruptions to ensure the safe operation of EHL-2.This paper evaluates the performance requirements of the disruption prediction system on EHL-2,with a particular focus on applying generalizable knowledge transfer from existing devices to future ones.Furthermore,the key characteristics of disruption mitigation strategies are analyzed,and their overall mitigation performance on EHL-2 is assessed.This insight provides valuable guidance for optimizing the engineering design of EHL-2 and identifying its optimal operational regime.
基金supported by the CAMS Innovation Fund for Medical Sciences(No.2023-I2M-3-019)National Natural Science Foundation of China(No.82404366)。
文摘In May 2018,the Director-General of the World Health Organization(WHO)called for global action to eliminate cervical cancer~1.This call marked the beginning of an ambitious international effort to scale up 3 key strategies:human papillomavirus(HPV)vaccination,cervical cancer screening,and treatment of precancerous lesions and cancer.Subsequently,the WHO and its partners developed a global strategy to accelerate the reduction of cervical cancer incidence,with an ultimate goal of achieving elimination within the next century.This Global Strategy represents a formal international commitment and is anchored in the 90-70-90 targets to be achieved by 2030.In parallel,several countries have also set national commitments,such as Sweden's pledge to achieve elimination by 2027 and Australia's target of achieving elimination by 2035.
基金supported by the National Natural Science Foundation of China(Grants No.41931293,42271279,42293271,and 41801175).
文摘China has achieved the poverty reduction goal of the United Nations 2030 Agenda for Sustainable Development 10 years ahead of schedule,contributing significantly to global poverty reduction.Despite extended efforts in poverty elimination,there is a lack of quantitative studies categorizing and comparing poverty-elimination counties(PECs)based on their processes.This study proposes an innovative framework for analyzing PECs’development paths from the perspective of population-land-industry(PLI).We quantify the PLI matching degree of PECs in China during the critical phase of the battle against poverty through a multivariate matching model,classify PECs via K-means clustering according to the consistency in PLI matching degree evolution,and summarize the typical development patterns of PECs.Results indicate that the PLI matching degree of PECs in China increased substantially from 2015 to 2020,particularly in eastern areas,while the western region,including the Qinghai-Xizang Plateau and southwestern Xinjiang,shows untapped potential for improvement.Five types of PECs are identified,with the majority(30.1%)showing sustained moderate PLI matching and a minority(9.6%)experiencing long-term PLI mismatch.Industry is the shortfall of various PECs,and effective strategies to facilitate all types of PECs include the development of emerging businesses and the expansion of secondary and tertiary industries.Additionally,enriching rural labor force and increasing farmland use efficiency are essential for optimal PLI matching and positive interaction,ultimately ensuring poverty elimination and sustainable development.
文摘The explosive expansion of the Internet of Things(IoT)systems has increased the imperative to have strong and robust solutions to cyber Security,especially to curtail Distributed Denial of Service(DDoS)attacks,which can cripple critical infrastructure.The proposed framework presented in the current paper is a new hybrid scheme that induces deep learning-based traffic classification and blockchain-enabledmitigation tomake intelligent,decentralized,and real-time DDoS countermeasures in an IoT network.The proposed model fuses the extracted deep features with statistical features and trains them by using traditional machine-learning algorithms,which makes them more accurate in detection than statistical features alone,based on the Convolutional Neural Network(CNN)architecture,which can extract deep features.A permissioned blockchain will be included to record the threat cases immutably and automatically execute mitigation measures through smart contracts to provide transparency and resilience.When tested on two test sets,BoT-IoT and IoT-23,the framework obtains a maximum F1-score at 97.5 percent and only a 1.8 percent false positive rate,which compares favorably to other solutions regarding effectiveness and the amount of time required to respond.Our findings support the feasibility of our method as an extensible and secure paradigm of nextgeneration IoT security,which has constrictive utility in mission-critical or resource-constrained settings.The work is a substantial milestone in autonomous and trustful mitigation against DDoS attacks through intelligent learning and decentralized enforcement.
文摘The excessive use of artificial intelligence(AI)algorithms has caused the problem of errors in AI algorithms,which has challenged the fairness of decision-making,and has intensified people’s inequality.Therefore,it is necessary to conduct in-depth research and propose corresponding error detection and error elimination methods.This paper first proposes the root causes and threats of bias in AI algorithms,then summarizes the existing bias detection and error elimination methods,and proposes a bias processing framework in three-level dimensions of data,models,and conclusions,aiming to provide a framework for a comprehensive solution to errors in algorithms.At the same time,it also summarizes the problems and challenges in existing research and makes a prospect for future research trends.It is hoped that it will be helpful for us to build fairer AI.
基金co-supported by the Tianjin Research innovation Project for Postgraduate Students,China(No.2022BKYZ039)the China Postdoctoral Science Foundation(No.2023M731788)the National Natural Science Foundation of China(No.62303246)。
文摘Global Navigation Satellite Systems(GNSSs)face significant security threats from spoofing attacks.Typical anti-spoofing methods rely on estimating the delays between spoofing and authentic signals using multicorrelator outputs.However,the accuracy of the delay estimation is limited by the spacing of the correlators.To address this,an innovative anti-spoofing method is introduced,which incorporates distinct coarse and refined stages for more accurate spoofing estimation.By leveraging the coarse delay estimates obtained through maximum likelihood estimation,the proposed method establishes the Windowed Sum of the Relative Delay(WSRD)statistics to detect the presence of spoofing signals.The iterative strategy is then employed to enhance the precision of the delay estimation.To further adapt to variations in the observation noise caused by spoofing intrusions and restore precise position,velocity,and timing solutions,an adaptive extended Kalman filter is proposed.This comprehensive framework offers detection,mitigation,and recovery against spoofing attacks.Experimental validation using datasets from the Texas Spoofing Test Battery(TEXBAT)demonstrates the effectiveness of the proposed anti-spoofing method.With 41 correlators,the method achieves a detection rate exceeding 90%at a false alarm rate of 10-5,with position or time errors below 15 m.Notably,this refined anti-spoofing approach shows robust detection and mitigation capabilities,requiring only a single antenna without the need for additional external sensors.These advancements can significantly contribute to the development of GNSS anti-spoofing measures.
基金supported by the National Natural Science Foundation of China(Grant No.42004103)Sichuan Science and Technology Program(2023NSFSC0257)the CNPC Innovation Found(2022DQ02-0306).
文摘Internal multiple interference,affecting both seismic data processing and interpretation,has been observed for long time.Although great progress has been achieved in developing a variety of internal-multiple-elimination(IME)methods,how to increase accuracy and reduce cost of IME still poses a significant challenge.A new method is proposed to effectively and efficiently eliminate internal multi-ples,along with its application in internal-multiple-eliminated-migration(IMEM),addressing this issue.This method stems from two-way wave equation depth-extrapolation scheme and associated up/down wavefield separation,which can accomplish depth-extrapolation of both up-going and down-going wavefields simultaneously,and complete internal-multiple-elimination processing,adaptively and effi-ciently.The proposed method has several features:(1)input data is same as that for conventional migration:source signature(used for migration only),macro velocity model,and receiver data,without additional requirements for source/receiver sampling;(2)method is efficient,without need of iterative calculations(which are typically needed for most of IME algorithms);and(3)method is cost effective:IME is completed in the same depth-extrapolation scheme of IMEM,without need of a separate pro-cessing and additional cost.Several synthesized data models are used to test the proposed method:one-dimensional model,horizontal layered model,multi-layer model with one curved layer,and SEG/EAGE Salt model.Additionally,we perform a sensitivity analysis of velocity using smoothed models.This analysis reveals that although the accuracy of velocity measurements impacts our proposed method,it significantly reduces internal multiple false imaging compared to traditional RTM techniques.When applied to actual seismic data from a carbonate reservoir zone,our method demonstrates superior clarity in imaging results,even in the presence of high-velocity carbonate formations,outperforming conven-tional migration methods in deep strata.
