The temperature of an organism provides key insights into its physiological and pathological status.Temperature monitoring can effectively assess potential health issues and plays a critical role in thermal treatment....The temperature of an organism provides key insights into its physiological and pathological status.Temperature monitoring can effectively assess potential health issues and plays a critical role in thermal treatment.Photoacoustic imaging(PAI)has enabled multi-scale imaging,from cells to tissues and organs,where its high contrast,deep penetration,and high resolution make it an emerging tool in biomedical imaging field.Benefiting from the linear correlation between the Grüneisen parameter and temperature within the range of 10–55∘C,the PAI has been developed as novel noninvasive label-free tool for temperature monitoring especially for thermotherapy mediated by laser,ultrasound,and microwave.Additionally,by utilizing temperature-responsive photoacoustic nanoprobes,the temperature information of the targeted organism can also be extracted with enhanced imaging contrast and specificity.This review elucidates the basic principles of temperature monitoring technology implemented by PAI,further highlighting the limitations of traditional photoacoustic thermometry,and summarizes recent technological advancements in analog simulation,calibration method,measurement accuracy,nanoprobe design,and wearable improvement.Furthermore,we discuss the biomedical applications of PA temperature monitoring technology in photothermal therapy and ultrasound therapy,finally,anticipating future developments in the field.展开更多
High-density permanent magnet synchronous motors(PMSMs) are widely used in electric drive systems. However, they are susceptible to temperature influences under complex operating conditions, and prolonged operation at...High-density permanent magnet synchronous motors(PMSMs) are widely used in electric drive systems. However, they are susceptible to temperature influences under complex operating conditions, and prolonged operation at high temperatures can first damage the stator winding insulation, which in turn will damage the windings themselves and cause faults. Therefore, stator temperature monitoring is of crucial importance. This paper summarizes the existing temperature monitoring technologies for stator windings of permanent magnet motors, compares the advantages and disadvantages of various methods to help researchers understand this technology, and analyzes its opportunities and challenges, followed by an outlook.展开更多
Flexible wearable optoelectronic devices fabricated fromorganic–inorganic hybrid perovskites significantly accelerate the developmentof portable energy,biomedicine,and sensing fields,but their poor thermal stabilityh...Flexible wearable optoelectronic devices fabricated fromorganic–inorganic hybrid perovskites significantly accelerate the developmentof portable energy,biomedicine,and sensing fields,but their poor thermal stabilityhinders further applications.Conversely,all-inorganic perovskites possessexcellent thermal stability,but black-phase all-inorganic perovskite filmusually requires high-temperature annealing steps,which increases energy consumptionand is not conducive to the fabrication of flexible wearable devices.In this work,an unprecedented low-temperature fabrication of stable blackphaseCsPbI3perovskite films is demonstrated by the in situ hydrolysis reactionof diphenylphosphinic chloride additive.The released diphenyl phosphateand chloride ions during the hydrolysis reaction significantly lower the phasetransition temperature and effectively passivate the defects in the perovskitefilms,yielding high-performance photodetectors with a responsivity of 42.1 AW−1 and a detectivity of 1.3×10^(14)Jones.Furthermore,high-fidelity imageand photoplethysmography sensors are demonstrated based on the fabricated flexible wearable photodetectors.This work provides a newperspective for the low-temperature fabrication of large-area all-inorganic perovskite flexible optoelectronic devices.展开更多
Wearable thermoelectric devices hold significant promise in the realm of self-powered wearable electron-ics,offering applications in energy harvesting,movement tracking,and health monitoring.Nevertheless,developing th...Wearable thermoelectric devices hold significant promise in the realm of self-powered wearable electron-ics,offering applications in energy harvesting,movement tracking,and health monitoring.Nevertheless,developing thermoelectric devices with exceptional flexibility,enduring thermoelectric stability,multi-functional sensing,and comfortable wear remains a challenge.In this work,a stretchable MXene-based thermoelectric fabric is designed to accurately discern temperature and strain stimuli.This is achieved by constructing an adhesive polydopamine(PDA)layer on the nylon fabric surface,which facilitates the subsequent MXene attachment through hydrogen bonding.This fusion results in MXene-based thermo-electric fabric that excels in both temperature sensing and strain sensing.The resultant MXene-based thermoelectric fabric exhibits outstanding temperature detection capability and cyclic stability,while also delivering excellent sensitivity,rapid responsiveness(60 ms),and remarkable durability in strain sens-ing(3200 cycles).Moreover,when affixed to a mask,this MXene-based thermoelectric fabric utilizes the temperature difference between the body and the environment to harness body heat,converting it into electrical energy and accurately discerning the body’s respiratory rate.In addition,the MXene-based ther-moelectric fabric can monitor the state of the body’s joint through its own deformation.Furthermore,it possesses the capability to convert solar energy into heat.These findings indicate that MXene-based ther-moelectric fabric holds great promise for applications in power generation,motion tracking,and health monitoring.展开更多
Enhancing the firefighting protective clothing with exceptional thermal barrier and temperature sensing functions to ensure high fire safety for firefighters has long been anticipated,but it remains a major challenge....Enhancing the firefighting protective clothing with exceptional thermal barrier and temperature sensing functions to ensure high fire safety for firefighters has long been anticipated,but it remains a major challenge.Herein,inspired by the human muscle,an anisotropic fire safety aerogel(ACMCA)with precise self-actuated temperature monitoring performance is developed by combining aramid nanofibers with eicosane/MXene to form an anisotropically oriented conductive network.By combining the two synergies of the negative temperaturedependent thermal conductive eicosane,which induces a high-temperature differential,and directionally ordered MXene that establishes a conductive network along the directional freezing direction.The resultant ACMCA exhibited remarkable thermoelectric properties,with S values reaching 46.78μV K^(−1)andκvalues as low as 0.048 W m^(−1)K^(−1)at room temperature.Moreover,the prepared anisotropic aerogel ACMCA exhibited electrical responsiveness to temperature variations,facilitating its application in intelligent temperature monitoring systems.The designed anisotropic aerogel ACMCA could be incorporated into the firefighting clothing as a thermal barrier layer,demonstrating a wide temperature sensing range(50-400℃)and a rapid response time for early high-temperature alerts(~1.43 s).This work provides novel insights into the design and application of temperature-sensitive anisotropic aramid nanofibers aerogel in firefighting clothing.展开更多
The Dazu Rock Carvings in Chongqing were inscribed on the World Heritage List in 1999.In recent years,the Dazu Rock Carvings have faced environmental challenges such as geological forces,increased precipitation,pollut...The Dazu Rock Carvings in Chongqing were inscribed on the World Heritage List in 1999.In recent years,the Dazu Rock Carvings have faced environmental challenges such as geological forces,increased precipitation,pollution and tourism,which have led to rock deterioration and structural instability.The multi-source monitoring system for the protection of the rock carvings,based on the Internet of Things,includes Global Navigation Satellite System(GNSS)displacement monitoring,static level displacement monitoring,laser rangefinder displacement monitoring,roof pressure sensor monitoring and environmental damage monitoring.This paper analyses data from each sub-monitoring system within the multi-source monitoring system applied to Yuanjue Cave in the Dazu Rock Carvings.Initially,a correlation analysis between climate monitoring data and roof displacement data was carried out to assess the effect of temperature.Based on the results of the analysis,a temperature correction equation for the laser rangefinder was derived to improve the laser rangefinder displacement monitoring system.The improved system was then used to monitor Cave 168,revealing the deformation and erosion patterns of the roof.The research results demonstrate that the multiparameter monitoring system is capable of accurately measuring and analyzing the stability of the Dazu stone carvings,as well as the effects of environmental conditions on them.The use of the Internet of Things(IoT)and real-time data collection to monitor rock deformation and environmental conditions is an innovative application of technology in cultural heritage conservation.Interpretation of the monitoring system and statistical correlation analysis of temperature and laser rangefinder data highlight the thoroughness of the methodology in this paper and its relevance to sustainable mountain development.In the future,multi-source monitoring systems will have a broader application in the conservation of other UNESCO World Heritage Sites.展开更多
Mineral resources exploitation moving deeper into the earth is an inevitable trend with economic and social development.However,the deep high temperature poses a significant challenge to the safety and efficiency of h...Mineral resources exploitation moving deeper into the earth is an inevitable trend with economic and social development.However,the deep high temperature poses a significant challenge to the safety and efficiency of human and machine.The prevention of potential thermal risks in deep mining is critical.Here,the key and difficult issues of humanmachine-environment temperature monitoring are discussed according to the characteristics of deep hightemperature environment.Then,a monitoring and analysis method of human-machine-environment temperature field suitable for deep high-temperature mining areas is proposed.This method covers humanmachine-environment temperature monitoring,data storage and transmission,data processing,results visualization,and thermal risks warning.The monitoring sensor networks are constructed to collect real-time data of miners,machines,and environments.The data is transmitted to the central processing system for storage and analysis using both wired and wireless transmission technologies.Moreover,digital filtering and Kriging interpolation algorithms are applied to denoise and handle outliers in the monitored data,as well as to calculate the temperature field.The temperature prediction model is constructed using Long Short-Term Memory(LSTM)method.Finally,potential thermal risks are identified by combining real-time monitoring and prediction results,thereby guiding management personnels and miners to take appropriate measures.The proposed monitoring and analysis method can be applied to deep mines that affected by high temperature.It not only provides data and methodological support for assessing thermal risks in mines,but also offers scientific basis for optimizing mining operations and implementing safety measures.展开更多
Purpose–This study solves the key problem that the static level monitoring is susceptible to temperature interference and affects the accuracy in slope instability/deformation monitoring.The purpose is to develop a r...Purpose–This study solves the key problem that the static level monitoring is susceptible to temperature interference and affects the accuracy in slope instability/deformation monitoring.The purpose is to develop a reliable temperature compensation method for the system,improve the accuracy of slope stability monitoring and provide support for improving the safety and safety monitoring of engineering spoil slope and other projects.Design/methodology/approach–Combined with theoretical analysis and experimental verification,the temperature compensation method is explored.The working principle of the hydrostatic leveling monitoring system is analyzed and the data processing formula,the temperature error calculation formula and the calculation formula for eliminating the error settlement value are derived.The temperature compensation method is established and verified by the field test of the engineering spoil slope which is disturbed by a debris flow.Findings–The experimental results show that this method can reduce the error of the static level monitoring system by about 40%.The field test shows that the fluctuation of slope settlement monitoring value is reduced after temperature compensation and the monitoring value is consistent with the actual situation,which has certain practicability.Originality/value–The originality of this study is to derive a theoretical formula for quantifying/eliminating temperature errors in static leveling and to establish a practical temperature compensation method.The accuracy of the system is improved,which provides a reference for slope stability monitoring under complex environment(especially railway geotechnical engineering)and promotes the development of precision monitoring technology.展开更多
To examine stress redistribution phenomena in bridges subjected to varying operational conditions,this study conducts a comprehensive analysis of three years of monitoring data from a 153-m double-deck road–rail stee...To examine stress redistribution phenomena in bridges subjected to varying operational conditions,this study conducts a comprehensive analysis of three years of monitoring data from a 153-m double-deck road–rail steel arch bridge.An initial statistical comparison of sensor data distributions reveals clear temporal variations in stress redistribution patterns.XGBoost(eXtreme Gradient Boosting),a gradient-boosting machine learning(ML)algorithm,was employed not only for predictive modeling but also to uncover the underlying mechanisms of stress evolution.Unlike traditional numerical models that rely on extensive assumptions and idealizations,XGBoost effectively captures nonlinear and time-varying relationships between stress states and operational/environmental factors,such as temperature,traffic load,and structural geometry.This approach allows for the identification of critical periods and conditions under which stress redistribution becomes significant.Results indicate a clear shift of stress concentrations frombeamends toward mid-span regions following the commencement of metro operations,reflecting both structural adaptation and localized overstress near arch ribs.Furthermore,the model generates robust predictions of stress evolution,demonstrating potential applications in early warning systems and fatigue risk assessment.This work represents the first application of interpretable gradient-boosting techniques to stress redistribution modeling in double-deck bridges.In addition,a Stress Redistribution Index(SRI)is proposed,derived from this monitoring study and finite-element-based transverse load distributions,to quantify temporal stress shifts between midspan and edge beams.The results provide both theoretical contributions and practical guidance for the design,inspection,and maintenance of complex bridge structures.展开更多
The 1.55μm laser technology is widely applied in military,information communication,biomedicine and other fields.With the deepening development of these application areas,the demand for novel 1.55μm laser gain media...The 1.55μm laser technology is widely applied in military,information communication,biomedicine and other fields.With the deepening development of these application areas,the demand for novel 1.55μm laser gain media is becoming increasingly urgent.This study reports a novel Yb^(3+),Er^(3+)co-doped KBa_(0.94)Ca_(0.06)Y(MoO_(4))_(3) (KBCYM)crystal.In this crystal,Yb^(3+)serves as a sensitizer,significantly enhancing the emission intensity of Er^(3+)in both visible and near-infrared bands.Notably,when the concentration of Yb^(3+)reaches 6 mol%,the emission intensity peaks at 1.55μm.Optical cross-section calculations reveal that the crystal exhibits a low laser pumping threshold at this concentration,demonstrating its potential as a laser gain medium.However,the crystal inevitably generates thermal effects during operation,which may adversely affect its performance.Therefore,real-time monitoring of the operating temperature is crucial.The thermal stability of the crystal was evaluated by measuring the temperature dependence of its luminescence intensity in the near-infrared band.Remarkably,even when the temperature rises to 553 K,the emission intensity at 1.55μm only decreases by 10.9%.Additionally,the temperature sensing performance was evaluated using fluorescence intensity ratio techniques,yielding absolute and relative sensitivities of 0.00981 K^(-1)at 453 K and 1.32%/K at 303 K,respectively,highlighting its potential for optical temperature sensing.Finally,through leveraging the unique properties of Yb^(3+),Er^(3+):KBCYM crystals,we successfully developed 1.55μm luminescent optical devices with practical applications.These devices not only exhibit efficient luminescent performance,but also possess a self-temperature measu rement functio n,opening up new avenues for the further development of laser technology.展开更多
Platinum group metals have high melting points,strong corrosion resistance,stable chemical properties,and low oxygen permeability in high-temperature oxygen-containing environments.As thermal protective coating materi...Platinum group metals have high melting points,strong corrosion resistance,stable chemical properties,and low oxygen permeability in high-temperature oxygen-containing environments.As thermal protective coating materials,they have gained essential applications in the aerospace field and have excellent prospects for application in frontier military fields,such as protecting hot-end components of hypersonic aircraft.This research reviewed the latest research progress of platinum group metal coatings with hightemperature oxidation resistance,including coating preparation techniques,oxidation failure,and alloying modification.The leading preparation techniques of current platinum group metal coatings were discussed,as well as the advantages and disadvantages of various existing preparation techniques.Besides,the intrinsic properties,failure forms,and failure mechanisms of coatings of single platinum group metal in high-temperature oxygen-containing environments were analyzed.On this basis,the necessity,main methods,and main achievements of alloying modification of platinum group metals were summarized.Finally,the future development of platinum group coatings with high-temperature oxidation resistance was discussed and prospected.展开更多
Lin Wei is a hiking enthusiast.At six o'clock on the last Saturday morning,the temperature at the foot of the mountain was only 2℃,so she put on her thickest fleece jacket.However,after only half an hour of climb...Lin Wei is a hiking enthusiast.At six o'clock on the last Saturday morning,the temperature at the foot of the mountain was only 2℃,so she put on her thickest fleece jacket.However,after only half an hour of climbing,the heat left her drenched in sweat,making her feel very cold.By midday,the temperature was approaching 20℃,and her heavy jacket had to be tied around her waist,becoming a burden during her hike.This outdoor adventure allowed her to appreciate the beautiful scenery,but also subjected her to repeated changes in temperature.展开更多
An innovative real-time monitoring method for surrounding rock damage based on microseismic time-lapse double-difference tomography is proposed for delayed dynamic damage identification and insufficient detection of a...An innovative real-time monitoring method for surrounding rock damage based on microseismic time-lapse double-difference tomography is proposed for delayed dynamic damage identification and insufficient detection of adverse geological conditions in deep-buried tunnel construction.The installation techniques for microseismic sensors were optimized by mounting sensors at bolt ends which significantly improves signal-to-noise ratio(SNR)and anti-interference capability compared to conventional borehole placement.Subsequently,a 3D wave velocity evolution model that incorporates construction-induced disturbances was established,enabling the first visualization of spatiotemporal variations in surrounding rock wave velocity.It finds significant wave velocity reduction near the tunnel face,with roof and floor damage zones extending 40–50 m;wave velocities approaching undisturbed levels at 15 m ahead of the working face and on the laterally undisturbed side;pronounced spatial asymmetry in wave velocity distribution—values on the left side exceed those on the right,with a clear stress concentration or transition zone located 10–15 m;and systematically lower velocities behind the face than in front,indicating asymmetric rock damage development.These results provide essential theoretical support and practical guidance for optimizing dynamic construction strategies,enabling real-time adjustment of support parameters,and establishing safety early warning systems in deep-buried tunnel engineering.展开更多
Traditional grade-centered evaluation models are inadequate for high-quality software engineering talents in the digital and AI era.This study develops an academic development monitoring system to address shortcomings...Traditional grade-centered evaluation models are inadequate for high-quality software engineering talents in the digital and AI era.This study develops an academic development monitoring system to address shortcomings in dynamics,interdisciplinary integration,and industry adaptability.It builds a multi-dimensional dynamic model covering seven core dimensions with quantitative scoring,non-linear weighting,and DivClust grouping.An intelligent platform with real-time monitoring,early warning,and personalized recommendations integrates AI like multi-modal fusion and large-model diagnosis.The“monitoring-warning-improvement”loop helps optimize training programs,support personalized planning,and bridge talent-industry gaps,enabling digital transformation in software engineering education evaluation.展开更多
It is well recognized that Structural Health Monitoring(SHM)reliability evaluation is a key aspect that needs to be urgently addressed to promote the wide application of SHM methods.However,the existing studies typica...It is well recognized that Structural Health Monitoring(SHM)reliability evaluation is a key aspect that needs to be urgently addressed to promote the wide application of SHM methods.However,the existing studies typically transfer the Non-Destructive Testing/Evaluation(NDT/E)reliability metrics to SHM without a systematic analysis of where these metrics originated.Seldom attentions are paid to the evaluation conditions which are very important to apply these metrics.Aimed at this issue,a new condition control-based Dual-Reliability Evaluation(Dual-RE)method for SHM is proposed.This new method is proposed based on a systematic analysis of the whole framework of reliability evaluation from instrument to NDT,and emphasis is paid to the evaluation condition control.Based on these analyses,considering the special online application scenario of SHM,the proposed Dual-RE method contains two key components:Integrated Sensor-based SHM-RE(IS-SHM-RE)and Critical Service Condition-based SHM-RE(CSC-SHM-RE).ISSHM-RE evaluates the reliability of integrated SHM sensor and system themselves under approximate repeatability conditions,while CSC-SHM-RE assesses SHM reliability under the dominant uncertainties during service,namely intermediate conditions.To demonstrate the Dual-RE,crack monitoring by using the Guided Wave-based-SHM(GW-SHM)on aircraft lug structures is taken as a case study.Both the crack detection and sizing performance are evaluated from accuracy and uncertainty.展开更多
In recent years,the research on superconductivity in one-dimensional(1D)materials has been attracting increasing attention due to its potential applications in low-dimensional nanodevices.However,the critical temperat...In recent years,the research on superconductivity in one-dimensional(1D)materials has been attracting increasing attention due to its potential applications in low-dimensional nanodevices.However,the critical temperature(T_(c))of 1D superconductors is low.In this work,we theoretically investigate the possible high T_(c) superconductivity of(5,5)carbon nanotube(CNT).The pristine(5,5)CNT is a Dirac semimetal and can be modulated into a semiconductor by full hydrogenation.Interestingly,by further hole doping,it can be regulated into a metallic state with the sp^(3)-hybridized σ electrons metalized,and a giant Kohn anomaly appears in the optical phonons.The two factors together enhance the electron–phonon coupling,and lead to high-T_(c) superconductivity.When the hole doping concentration of hydrogenated-(5,5)CNT is 2.5 hole/cell,the calculated T_(c) is 82.3 K,exceeding the boiling point of liquid nitrogen.Therefore,the predicted hole-doped hydrogenated-(5,5)CNT provides a new platform for 1D high-T_(c) superconductivity and may have potential applications in 1D nanodevices.展开更多
To advance the theoretical understanding,technological development,and field application of electric charge induction for monitoring rock deformation and failure,this study investigates the induced electric charge gen...To advance the theoretical understanding,technological development,and field application of electric charge induction for monitoring rock deformation and failure,this study investigates the induced electric charge generated during the deformation and failure of igneous rocks.The charge originates mainly from a combination of electrical polarization and triboelectric effects.Through laboratory experiments,we analyzed the time-frequency evolution of induced electric charge signals and identified relevant monitoring parameters.An online downhole electric charge induction monitoring system was developed and validated in the field.Experimental results show that the dominant frequency range of induced electric charge signals generated during igneous rock deformation and failure lies between 0 and 23 Hz,and a low-pass finite impulse response(FIR)filter effectively suppresses noise.Optimal sensor distances for monitoring cubic and cylindrical specimens were determined to be 17 mm and 13 mm,respectively.We proposed early warning indicators,including the maximum absolute value of the induced electric charge,the arithmetic mean value,the distribution dispersion coefficient,and the cumulative sum value.In field application,time-domain curves and spatial distribution charts of these warning indicators correspond well with changes in abutment stress ahead of the mining face,offering indirect insights into local stress evolution.This research provides technical and equipment support for the application of electric charge induction technology to monitoring and early warning of coal bursts.展开更多
A rapidly growing field is piezoresistive sensor for accurate respiration rate monitoring to suppress the worldwide respiratory illness.However,a large neglected issue is the sensing durability and accuracy without in...A rapidly growing field is piezoresistive sensor for accurate respiration rate monitoring to suppress the worldwide respiratory illness.However,a large neglected issue is the sensing durability and accuracy without interference since the expiratory pressure always coupled with external humidity and temperature variations,as well as mechanical motion artifacts.Herein,a robust and biodegradable piezoresistive sensor is reported that consists of heterogeneous MXene/cellulose-gelation sensing layer and Ag-based interdigital electrode,featuring customizable cylindrical interface arrangement and compact hierarchical laminated architecture for collectively regulating the piezoresistive response and mechanical robustness,thereby realizing the long-term breath-induced pressure detection.Notably,molecular dynamics simulations reveal the frequent angle inversion and reorientation of MXene/cellulose in vacuum filtration,driven by shear forces and interfacial interactions,which facilitate the establishment of hydrogen bonds and optimize the architecture design in sensing layer.The resultant sensor delivers unprecedented collection features of superior stability for off-axis deformation(0-120°,~2.8×10^(-3) A)and sensing accuracy without crosstalk(humidity 50%-100%and temperature 30-80).Besides,the sensor-embedded mask together with machine learning models is achieved to train and classify the respiration status for volunteers with different ages(average prediction accuracy~90%).It is envisioned that the customizable architecture design and sensor paradigm will shed light on the advanced stability of sustainable electronics and pave the way for the commercial application in respiratory monitory.展开更多
Spikelet filling characteristics in early-season rice in southern China may be distinctive due to its exposure to high temperatures during the ripening period.However,limited information is currently available on thes...Spikelet filling characteristics in early-season rice in southern China may be distinctive due to its exposure to high temperatures during the ripening period.However,limited information is currently available on these characteristics.This study aimed to characterize spikelet filling in early-season rice and identify the key factors contributing to its improvement.Field experiments were conducted over two years(2021 and 2022)to mainly investigate the proportions of fully-filled,partially-filled,and empty spikelets,along with the biomass-fertilized spikelet ratio and harvest index,in 11 early-season rice varieties.The results revealed significant varietal variation in spikelet filling,with the proportion of fully-filled spikelets ranging from 60.6%to 81.1%in 2021 and from 66.3%to 79.2%in 2022.Among the 11 varieties,Liangyou 42,Lingliangyou 942,and Liangyou 287 exhibited relatively superior performance in spikelet filling.Linear regression revealed that,although a significant negative relationship existed between the proportion of fully-filled spikelets and both partially-filled and empty spikelets,the relationship with partially-filled spikelets was stronger.Additionally,the proportion of fully-filled spikelets showed a significant positive relationship with the harvest index but not with the biomass-fertilized spikelet ratio.These findings indicate that increasing the harvest index and reducing the occurrence of partially-filled grains are essential strategies for improving spikelet filling in early-season rice.展开更多
The effective early warning of surrounding rock mass deformation is crucial in geotechnical engineering for ensuring the safety and stability of underground constructions.This study introduces a novel risk early warni...The effective early warning of surrounding rock mass deformation is crucial in geotechnical engineering for ensuring the safety and stability of underground constructions.This study introduces a novel risk early warning model based on multi-parameter fuzzy comprehensive evaluation,which quantitatively assesses the risk state of the surrounding rock mass.The microseismic(MS)monitoring system is set up for the underground powerhouse.The spatial and temporal distribution of MS events and the frequency characteristics of MS signals are analyzed during the top arch excavation.The early warning indices for characterizing MS spatial aggregation and frequency-energy dispersion are proposed based on the octree theory to assess the deformation of the surrounding rock mass.The risk warning model for the surrounding rock mass in underground engineering is developed through the integration of the formulated index and the frequency characteristics of MS signals.The results indicate that the multiparameter fuzzy comprehensive assessment model can achieve three-dimensional visualization of risk warnings for the surrounding rock mass.The quantitative results regarding warning time and potential deformation areas are highly consistent with the characteristics of MS precursors.These research results can provide an important reference for early warning of surrounding rock mass risk in similar underground projects.展开更多
基金supported by the National Natural Science Foundation of China(No.12174125)Guangdong Basic and Applied Basic Research Foundation(Nos.2024A1515010522 and 2021A1515011874).
文摘The temperature of an organism provides key insights into its physiological and pathological status.Temperature monitoring can effectively assess potential health issues and plays a critical role in thermal treatment.Photoacoustic imaging(PAI)has enabled multi-scale imaging,from cells to tissues and organs,where its high contrast,deep penetration,and high resolution make it an emerging tool in biomedical imaging field.Benefiting from the linear correlation between the Grüneisen parameter and temperature within the range of 10–55∘C,the PAI has been developed as novel noninvasive label-free tool for temperature monitoring especially for thermotherapy mediated by laser,ultrasound,and microwave.Additionally,by utilizing temperature-responsive photoacoustic nanoprobes,the temperature information of the targeted organism can also be extracted with enhanced imaging contrast and specificity.This review elucidates the basic principles of temperature monitoring technology implemented by PAI,further highlighting the limitations of traditional photoacoustic thermometry,and summarizes recent technological advancements in analog simulation,calibration method,measurement accuracy,nanoprobe design,and wearable improvement.Furthermore,we discuss the biomedical applications of PA temperature monitoring technology in photothermal therapy and ultrasound therapy,finally,anticipating future developments in the field.
基金supported by the National Key R&D Program of China (2021YFB2500600)。
文摘High-density permanent magnet synchronous motors(PMSMs) are widely used in electric drive systems. However, they are susceptible to temperature influences under complex operating conditions, and prolonged operation at high temperatures can first damage the stator winding insulation, which in turn will damage the windings themselves and cause faults. Therefore, stator temperature monitoring is of crucial importance. This paper summarizes the existing temperature monitoring technologies for stator windings of permanent magnet motors, compares the advantages and disadvantages of various methods to help researchers understand this technology, and analyzes its opportunities and challenges, followed by an outlook.
基金supported by the National Natural Science Foundation of China(52303257,52321006,T2394480,and T2394484)the National Key R&D Program of China(Grant No.2023YFE0111500)+3 种基金Key Research&Development and Promotion of Special Project(Scientific Problem Tackling)of Henan Province(242102211090)the China Postdoctoral Science Foundation(2023TQ0300,and 2023M743171)the Postdoctoral Fellowship Program(Grade B)of China Postdoctoral Science Foundation(GZB20230666)College Student Innovation and Entrepreneurship Training Program of Zhengzhou University(202410459200)。
文摘Flexible wearable optoelectronic devices fabricated fromorganic–inorganic hybrid perovskites significantly accelerate the developmentof portable energy,biomedicine,and sensing fields,but their poor thermal stabilityhinders further applications.Conversely,all-inorganic perovskites possessexcellent thermal stability,but black-phase all-inorganic perovskite filmusually requires high-temperature annealing steps,which increases energy consumptionand is not conducive to the fabrication of flexible wearable devices.In this work,an unprecedented low-temperature fabrication of stable blackphaseCsPbI3perovskite films is demonstrated by the in situ hydrolysis reactionof diphenylphosphinic chloride additive.The released diphenyl phosphateand chloride ions during the hydrolysis reaction significantly lower the phasetransition temperature and effectively passivate the defects in the perovskitefilms,yielding high-performance photodetectors with a responsivity of 42.1 AW−1 and a detectivity of 1.3×10^(14)Jones.Furthermore,high-fidelity imageand photoplethysmography sensors are demonstrated based on the fabricated flexible wearable photodetectors.This work provides a newperspective for the low-temperature fabrication of large-area all-inorganic perovskite flexible optoelectronic devices.
基金supported by the National Natural Science Foundation of China(No.21975107)the China Scholarship Council(No.202206790046).
文摘Wearable thermoelectric devices hold significant promise in the realm of self-powered wearable electron-ics,offering applications in energy harvesting,movement tracking,and health monitoring.Nevertheless,developing thermoelectric devices with exceptional flexibility,enduring thermoelectric stability,multi-functional sensing,and comfortable wear remains a challenge.In this work,a stretchable MXene-based thermoelectric fabric is designed to accurately discern temperature and strain stimuli.This is achieved by constructing an adhesive polydopamine(PDA)layer on the nylon fabric surface,which facilitates the subsequent MXene attachment through hydrogen bonding.This fusion results in MXene-based thermo-electric fabric that excels in both temperature sensing and strain sensing.The resultant MXene-based thermoelectric fabric exhibits outstanding temperature detection capability and cyclic stability,while also delivering excellent sensitivity,rapid responsiveness(60 ms),and remarkable durability in strain sens-ing(3200 cycles).Moreover,when affixed to a mask,this MXene-based thermoelectric fabric utilizes the temperature difference between the body and the environment to harness body heat,converting it into electrical energy and accurately discerning the body’s respiratory rate.In addition,the MXene-based ther-moelectric fabric can monitor the state of the body’s joint through its own deformation.Furthermore,it possesses the capability to convert solar energy into heat.These findings indicate that MXene-based ther-moelectric fabric holds great promise for applications in power generation,motion tracking,and health monitoring.
基金funding support from Guiding Project of Scientific Research Plan of Education Department of Hubei Province and Wuhan Textile University School Fund(B)(k24016).
文摘Enhancing the firefighting protective clothing with exceptional thermal barrier and temperature sensing functions to ensure high fire safety for firefighters has long been anticipated,but it remains a major challenge.Herein,inspired by the human muscle,an anisotropic fire safety aerogel(ACMCA)with precise self-actuated temperature monitoring performance is developed by combining aramid nanofibers with eicosane/MXene to form an anisotropically oriented conductive network.By combining the two synergies of the negative temperaturedependent thermal conductive eicosane,which induces a high-temperature differential,and directionally ordered MXene that establishes a conductive network along the directional freezing direction.The resultant ACMCA exhibited remarkable thermoelectric properties,with S values reaching 46.78μV K^(−1)andκvalues as low as 0.048 W m^(−1)K^(−1)at room temperature.Moreover,the prepared anisotropic aerogel ACMCA exhibited electrical responsiveness to temperature variations,facilitating its application in intelligent temperature monitoring systems.The designed anisotropic aerogel ACMCA could be incorporated into the firefighting clothing as a thermal barrier layer,demonstrating a wide temperature sensing range(50-400℃)and a rapid response time for early high-temperature alerts(~1.43 s).This work provides novel insights into the design and application of temperature-sensitive anisotropic aramid nanofibers aerogel in firefighting clothing.
基金financial support from the National Natural Science Foundation of China(No.42377154)。
文摘The Dazu Rock Carvings in Chongqing were inscribed on the World Heritage List in 1999.In recent years,the Dazu Rock Carvings have faced environmental challenges such as geological forces,increased precipitation,pollution and tourism,which have led to rock deterioration and structural instability.The multi-source monitoring system for the protection of the rock carvings,based on the Internet of Things,includes Global Navigation Satellite System(GNSS)displacement monitoring,static level displacement monitoring,laser rangefinder displacement monitoring,roof pressure sensor monitoring and environmental damage monitoring.This paper analyses data from each sub-monitoring system within the multi-source monitoring system applied to Yuanjue Cave in the Dazu Rock Carvings.Initially,a correlation analysis between climate monitoring data and roof displacement data was carried out to assess the effect of temperature.Based on the results of the analysis,a temperature correction equation for the laser rangefinder was derived to improve the laser rangefinder displacement monitoring system.The improved system was then used to monitor Cave 168,revealing the deformation and erosion patterns of the roof.The research results demonstrate that the multiparameter monitoring system is capable of accurately measuring and analyzing the stability of the Dazu stone carvings,as well as the effects of environmental conditions on them.The use of the Internet of Things(IoT)and real-time data collection to monitor rock deformation and environmental conditions is an innovative application of technology in cultural heritage conservation.Interpretation of the monitoring system and statistical correlation analysis of temperature and laser rangefinder data highlight the thoroughness of the methodology in this paper and its relevance to sustainable mountain development.In the future,multi-source monitoring systems will have a broader application in the conservation of other UNESCO World Heritage Sites.
基金supported by the National Science Foundation for Distinguished Young Scholars of China(Grant No.52425403)。
文摘Mineral resources exploitation moving deeper into the earth is an inevitable trend with economic and social development.However,the deep high temperature poses a significant challenge to the safety and efficiency of human and machine.The prevention of potential thermal risks in deep mining is critical.Here,the key and difficult issues of humanmachine-environment temperature monitoring are discussed according to the characteristics of deep hightemperature environment.Then,a monitoring and analysis method of human-machine-environment temperature field suitable for deep high-temperature mining areas is proposed.This method covers humanmachine-environment temperature monitoring,data storage and transmission,data processing,results visualization,and thermal risks warning.The monitoring sensor networks are constructed to collect real-time data of miners,machines,and environments.The data is transmitted to the central processing system for storage and analysis using both wired and wireless transmission technologies.Moreover,digital filtering and Kriging interpolation algorithms are applied to denoise and handle outliers in the monitored data,as well as to calculate the temperature field.The temperature prediction model is constructed using Long Short-Term Memory(LSTM)method.Finally,potential thermal risks are identified by combining real-time monitoring and prediction results,thereby guiding management personnels and miners to take appropriate measures.The proposed monitoring and analysis method can be applied to deep mines that affected by high temperature.It not only provides data and methodological support for assessing thermal risks in mines,but also offers scientific basis for optimizing mining operations and implementing safety measures.
基金funded by the Scientific Research Project of China Academy of Railway Sciences Group Co.,Ltd(No.2024YJ332 and No.2024QT005)Scientific Research Special Project of China State Railway Group Co.,Ltd(No.TICSTR-2024-Ⅳ-007).
文摘Purpose–This study solves the key problem that the static level monitoring is susceptible to temperature interference and affects the accuracy in slope instability/deformation monitoring.The purpose is to develop a reliable temperature compensation method for the system,improve the accuracy of slope stability monitoring and provide support for improving the safety and safety monitoring of engineering spoil slope and other projects.Design/methodology/approach–Combined with theoretical analysis and experimental verification,the temperature compensation method is explored.The working principle of the hydrostatic leveling monitoring system is analyzed and the data processing formula,the temperature error calculation formula and the calculation formula for eliminating the error settlement value are derived.The temperature compensation method is established and verified by the field test of the engineering spoil slope which is disturbed by a debris flow.Findings–The experimental results show that this method can reduce the error of the static level monitoring system by about 40%.The field test shows that the fluctuation of slope settlement monitoring value is reduced after temperature compensation and the monitoring value is consistent with the actual situation,which has certain practicability.Originality/value–The originality of this study is to derive a theoretical formula for quantifying/eliminating temperature errors in static leveling and to establish a practical temperature compensation method.The accuracy of the system is improved,which provides a reference for slope stability monitoring under complex environment(especially railway geotechnical engineering)and promotes the development of precision monitoring technology.
基金supported by the Key Technologies Research and Development Program under Grant 2021YFB1600300.
文摘To examine stress redistribution phenomena in bridges subjected to varying operational conditions,this study conducts a comprehensive analysis of three years of monitoring data from a 153-m double-deck road–rail steel arch bridge.An initial statistical comparison of sensor data distributions reveals clear temporal variations in stress redistribution patterns.XGBoost(eXtreme Gradient Boosting),a gradient-boosting machine learning(ML)algorithm,was employed not only for predictive modeling but also to uncover the underlying mechanisms of stress evolution.Unlike traditional numerical models that rely on extensive assumptions and idealizations,XGBoost effectively captures nonlinear and time-varying relationships between stress states and operational/environmental factors,such as temperature,traffic load,and structural geometry.This approach allows for the identification of critical periods and conditions under which stress redistribution becomes significant.Results indicate a clear shift of stress concentrations frombeamends toward mid-span regions following the commencement of metro operations,reflecting both structural adaptation and localized overstress near arch ribs.Furthermore,the model generates robust predictions of stress evolution,demonstrating potential applications in early warning systems and fatigue risk assessment.This work represents the first application of interpretable gradient-boosting techniques to stress redistribution modeling in double-deck bridges.In addition,a Stress Redistribution Index(SRI)is proposed,derived from this monitoring study and finite-element-based transverse load distributions,to quantify temporal stress shifts between midspan and edge beams.The results provide both theoretical contributions and practical guidance for the design,inspection,and maintenance of complex bridge structures.
基金Project supported by Jilin Provincial Department of Education(JJKH20230821KJ,JJKH20230822KJ,JJKH20230823KJ,JJKH20240930KJ,20240101107JC)。
文摘The 1.55μm laser technology is widely applied in military,information communication,biomedicine and other fields.With the deepening development of these application areas,the demand for novel 1.55μm laser gain media is becoming increasingly urgent.This study reports a novel Yb^(3+),Er^(3+)co-doped KBa_(0.94)Ca_(0.06)Y(MoO_(4))_(3) (KBCYM)crystal.In this crystal,Yb^(3+)serves as a sensitizer,significantly enhancing the emission intensity of Er^(3+)in both visible and near-infrared bands.Notably,when the concentration of Yb^(3+)reaches 6 mol%,the emission intensity peaks at 1.55μm.Optical cross-section calculations reveal that the crystal exhibits a low laser pumping threshold at this concentration,demonstrating its potential as a laser gain medium.However,the crystal inevitably generates thermal effects during operation,which may adversely affect its performance.Therefore,real-time monitoring of the operating temperature is crucial.The thermal stability of the crystal was evaluated by measuring the temperature dependence of its luminescence intensity in the near-infrared band.Remarkably,even when the temperature rises to 553 K,the emission intensity at 1.55μm only decreases by 10.9%.Additionally,the temperature sensing performance was evaluated using fluorescence intensity ratio techniques,yielding absolute and relative sensitivities of 0.00981 K^(-1)at 453 K and 1.32%/K at 303 K,respectively,highlighting its potential for optical temperature sensing.Finally,through leveraging the unique properties of Yb^(3+),Er^(3+):KBCYM crystals,we successfully developed 1.55μm luminescent optical devices with practical applications.These devices not only exhibit efficient luminescent performance,but also possess a self-temperature measu rement functio n,opening up new avenues for the further development of laser technology.
文摘Platinum group metals have high melting points,strong corrosion resistance,stable chemical properties,and low oxygen permeability in high-temperature oxygen-containing environments.As thermal protective coating materials,they have gained essential applications in the aerospace field and have excellent prospects for application in frontier military fields,such as protecting hot-end components of hypersonic aircraft.This research reviewed the latest research progress of platinum group metal coatings with hightemperature oxidation resistance,including coating preparation techniques,oxidation failure,and alloying modification.The leading preparation techniques of current platinum group metal coatings were discussed,as well as the advantages and disadvantages of various existing preparation techniques.Besides,the intrinsic properties,failure forms,and failure mechanisms of coatings of single platinum group metal in high-temperature oxygen-containing environments were analyzed.On this basis,the necessity,main methods,and main achievements of alloying modification of platinum group metals were summarized.Finally,the future development of platinum group coatings with high-temperature oxidation resistance was discussed and prospected.
文摘Lin Wei is a hiking enthusiast.At six o'clock on the last Saturday morning,the temperature at the foot of the mountain was only 2℃,so she put on her thickest fleece jacket.However,after only half an hour of climbing,the heat left her drenched in sweat,making her feel very cold.By midday,the temperature was approaching 20℃,and her heavy jacket had to be tied around her waist,becoming a burden during her hike.This outdoor adventure allowed her to appreciate the beautiful scenery,but also subjected her to repeated changes in temperature.
基金support of the National Natural Science Foundation of China(No.52274176)the Guangdong Province Key Areas R&D Program(No.2022B0101070001)+5 种基金Chongqing Elite Innovation and Entrepreneurship Leading talent Project(No.CQYC20220302517)the Chongqing Natural Science Foundation Innovation and Development Joint Fund(No.CSTB2022NSCQ-LZX0079)the National Key Research and Development Program Young Scientists Project(No.2022YFC2905700)the Chongqing Municipal Education Commission“Shuangcheng Economic Circle Construction in Chengdu-Chongqing Area”Science and Technology Innovation Project(No.KJCX2020031)the Fundamental Research Funds for the Central Universities(No.2024CDJGF-009)the Key Project for Technological Innovation and Application Development in Chongqing(No.CSTB2025TIAD-KPX0029).
文摘An innovative real-time monitoring method for surrounding rock damage based on microseismic time-lapse double-difference tomography is proposed for delayed dynamic damage identification and insufficient detection of adverse geological conditions in deep-buried tunnel construction.The installation techniques for microseismic sensors were optimized by mounting sensors at bolt ends which significantly improves signal-to-noise ratio(SNR)and anti-interference capability compared to conventional borehole placement.Subsequently,a 3D wave velocity evolution model that incorporates construction-induced disturbances was established,enabling the first visualization of spatiotemporal variations in surrounding rock wave velocity.It finds significant wave velocity reduction near the tunnel face,with roof and floor damage zones extending 40–50 m;wave velocities approaching undisturbed levels at 15 m ahead of the working face and on the laterally undisturbed side;pronounced spatial asymmetry in wave velocity distribution—values on the left side exceed those on the right,with a clear stress concentration or transition zone located 10–15 m;and systematically lower velocities behind the face than in front,indicating asymmetric rock damage development.These results provide essential theoretical support and practical guidance for optimizing dynamic construction strategies,enabling real-time adjustment of support parameters,and establishing safety early warning systems in deep-buried tunnel engineering.
基金supported by the Research Funding Project for Graduate Education and Teaching Reform of Beijing University of Posts and Telecommunications(No.2024Y036)the Postgraduate Education and Teaching Reform Research Fund Project of Beijing University of Posts and Telecommunications(No.2024Z007)the Postgraduate Education and Teaching Reform Project of Beijing University of Posts and Telecommunications(2025).
文摘Traditional grade-centered evaluation models are inadequate for high-quality software engineering talents in the digital and AI era.This study develops an academic development monitoring system to address shortcomings in dynamics,interdisciplinary integration,and industry adaptability.It builds a multi-dimensional dynamic model covering seven core dimensions with quantitative scoring,non-linear weighting,and DivClust grouping.An intelligent platform with real-time monitoring,early warning,and personalized recommendations integrates AI like multi-modal fusion and large-model diagnosis.The“monitoring-warning-improvement”loop helps optimize training programs,support personalized planning,and bridge talent-industry gaps,enabling digital transformation in software engineering education evaluation.
基金the support from National Natural Science Foundation of China(No.52275153)the Frontier Technologies R&D Program of Jiangsu,China(No.BF2024068)+1 种基金The Fund of Prospective Layout of Scientific Research for Nanjing University of Aeronautics and Astronautics,ChinaResearch Fund of State Key Laboratory of Mechanics and Control for Aerospace Structures(Nanjing University of Aeronautics and Astronautics),China(Nos.MCAS-I-0425K01,MCAS-I-0423G01)。
文摘It is well recognized that Structural Health Monitoring(SHM)reliability evaluation is a key aspect that needs to be urgently addressed to promote the wide application of SHM methods.However,the existing studies typically transfer the Non-Destructive Testing/Evaluation(NDT/E)reliability metrics to SHM without a systematic analysis of where these metrics originated.Seldom attentions are paid to the evaluation conditions which are very important to apply these metrics.Aimed at this issue,a new condition control-based Dual-Reliability Evaluation(Dual-RE)method for SHM is proposed.This new method is proposed based on a systematic analysis of the whole framework of reliability evaluation from instrument to NDT,and emphasis is paid to the evaluation condition control.Based on these analyses,considering the special online application scenario of SHM,the proposed Dual-RE method contains two key components:Integrated Sensor-based SHM-RE(IS-SHM-RE)and Critical Service Condition-based SHM-RE(CSC-SHM-RE).ISSHM-RE evaluates the reliability of integrated SHM sensor and system themselves under approximate repeatability conditions,while CSC-SHM-RE assesses SHM reliability under the dominant uncertainties during service,namely intermediate conditions.To demonstrate the Dual-RE,crack monitoring by using the Guided Wave-based-SHM(GW-SHM)on aircraft lug structures is taken as a case study.Both the crack detection and sizing performance are evaluated from accuracy and uncertainty.
基金supported by the National Natural Science Foundation of China (Grant Nos.12074213 and 11574108)the Major Basic Program of Natural Science Foundation of Shandong Province (Grant No.ZR2021ZD01)the Natural Science Foundation of Shandong Province (Grant No.ZR2023MA082)。
文摘In recent years,the research on superconductivity in one-dimensional(1D)materials has been attracting increasing attention due to its potential applications in low-dimensional nanodevices.However,the critical temperature(T_(c))of 1D superconductors is low.In this work,we theoretically investigate the possible high T_(c) superconductivity of(5,5)carbon nanotube(CNT).The pristine(5,5)CNT is a Dirac semimetal and can be modulated into a semiconductor by full hydrogenation.Interestingly,by further hole doping,it can be regulated into a metallic state with the sp^(3)-hybridized σ electrons metalized,and a giant Kohn anomaly appears in the optical phonons.The two factors together enhance the electron–phonon coupling,and lead to high-T_(c) superconductivity.When the hole doping concentration of hydrogenated-(5,5)CNT is 2.5 hole/cell,the calculated T_(c) is 82.3 K,exceeding the boiling point of liquid nitrogen.Therefore,the predicted hole-doped hydrogenated-(5,5)CNT provides a new platform for 1D high-T_(c) superconductivity and may have potential applications in 1D nanodevices.
基金supported by the National Key Research and Development Project of the National Natural Science Foundation of China(Grant No.2022YFC3004605)the National Natural Science Foundation of China Youth Science Fund(Grant No.52104087).
文摘To advance the theoretical understanding,technological development,and field application of electric charge induction for monitoring rock deformation and failure,this study investigates the induced electric charge generated during the deformation and failure of igneous rocks.The charge originates mainly from a combination of electrical polarization and triboelectric effects.Through laboratory experiments,we analyzed the time-frequency evolution of induced electric charge signals and identified relevant monitoring parameters.An online downhole electric charge induction monitoring system was developed and validated in the field.Experimental results show that the dominant frequency range of induced electric charge signals generated during igneous rock deformation and failure lies between 0 and 23 Hz,and a low-pass finite impulse response(FIR)filter effectively suppresses noise.Optimal sensor distances for monitoring cubic and cylindrical specimens were determined to be 17 mm and 13 mm,respectively.We proposed early warning indicators,including the maximum absolute value of the induced electric charge,the arithmetic mean value,the distribution dispersion coefficient,and the cumulative sum value.In field application,time-domain curves and spatial distribution charts of these warning indicators correspond well with changes in abutment stress ahead of the mining face,offering indirect insights into local stress evolution.This research provides technical and equipment support for the application of electric charge induction technology to monitoring and early warning of coal bursts.
基金supported by the National Natural Science Foundation of China(22074072,22274083,52376199)the Shandong Provincial Natural Science Foundation(ZR2023LZY005)+1 种基金the Exploration Project of the State Key Laboratory of BioFibers and EcoTextiles of Qingdao University(TSKT202101)the Fundamental Research Funds for the Central Universities(2022BLRD13,2023BLRD01).
文摘A rapidly growing field is piezoresistive sensor for accurate respiration rate monitoring to suppress the worldwide respiratory illness.However,a large neglected issue is the sensing durability and accuracy without interference since the expiratory pressure always coupled with external humidity and temperature variations,as well as mechanical motion artifacts.Herein,a robust and biodegradable piezoresistive sensor is reported that consists of heterogeneous MXene/cellulose-gelation sensing layer and Ag-based interdigital electrode,featuring customizable cylindrical interface arrangement and compact hierarchical laminated architecture for collectively regulating the piezoresistive response and mechanical robustness,thereby realizing the long-term breath-induced pressure detection.Notably,molecular dynamics simulations reveal the frequent angle inversion and reorientation of MXene/cellulose in vacuum filtration,driven by shear forces and interfacial interactions,which facilitate the establishment of hydrogen bonds and optimize the architecture design in sensing layer.The resultant sensor delivers unprecedented collection features of superior stability for off-axis deformation(0-120°,~2.8×10^(-3) A)and sensing accuracy without crosstalk(humidity 50%-100%and temperature 30-80).Besides,the sensor-embedded mask together with machine learning models is achieved to train and classify the respiration status for volunteers with different ages(average prediction accuracy~90%).It is envisioned that the customizable architecture design and sensor paradigm will shed light on the advanced stability of sustainable electronics and pave the way for the commercial application in respiratory monitory.
基金funded by the Earmarked Fund for China Agriculture Research System,grant number CARS-01-33.
文摘Spikelet filling characteristics in early-season rice in southern China may be distinctive due to its exposure to high temperatures during the ripening period.However,limited information is currently available on these characteristics.This study aimed to characterize spikelet filling in early-season rice and identify the key factors contributing to its improvement.Field experiments were conducted over two years(2021 and 2022)to mainly investigate the proportions of fully-filled,partially-filled,and empty spikelets,along with the biomass-fertilized spikelet ratio and harvest index,in 11 early-season rice varieties.The results revealed significant varietal variation in spikelet filling,with the proportion of fully-filled spikelets ranging from 60.6%to 81.1%in 2021 and from 66.3%to 79.2%in 2022.Among the 11 varieties,Liangyou 42,Lingliangyou 942,and Liangyou 287 exhibited relatively superior performance in spikelet filling.Linear regression revealed that,although a significant negative relationship existed between the proportion of fully-filled spikelets and both partially-filled and empty spikelets,the relationship with partially-filled spikelets was stronger.Additionally,the proportion of fully-filled spikelets showed a significant positive relationship with the harvest index but not with the biomass-fertilized spikelet ratio.These findings indicate that increasing the harvest index and reducing the occurrence of partially-filled grains are essential strategies for improving spikelet filling in early-season rice.
基金support from the Sichuan Science and Technology Program(Grant No.2023NSFSC0812).
文摘The effective early warning of surrounding rock mass deformation is crucial in geotechnical engineering for ensuring the safety and stability of underground constructions.This study introduces a novel risk early warning model based on multi-parameter fuzzy comprehensive evaluation,which quantitatively assesses the risk state of the surrounding rock mass.The microseismic(MS)monitoring system is set up for the underground powerhouse.The spatial and temporal distribution of MS events and the frequency characteristics of MS signals are analyzed during the top arch excavation.The early warning indices for characterizing MS spatial aggregation and frequency-energy dispersion are proposed based on the octree theory to assess the deformation of the surrounding rock mass.The risk warning model for the surrounding rock mass in underground engineering is developed through the integration of the formulated index and the frequency characteristics of MS signals.The results indicate that the multiparameter fuzzy comprehensive assessment model can achieve three-dimensional visualization of risk warnings for the surrounding rock mass.The quantitative results regarding warning time and potential deformation areas are highly consistent with the characteristics of MS precursors.These research results can provide an important reference for early warning of surrounding rock mass risk in similar underground projects.
