Flexible fiber sensors,However,traditional methods face challenges in fabricating low-cost,large-scale fiber sensors.In recent years,the thermal drawing process has rapidly advanced,offering a novel approach to flexib...Flexible fiber sensors,However,traditional methods face challenges in fabricating low-cost,large-scale fiber sensors.In recent years,the thermal drawing process has rapidly advanced,offering a novel approach to flexible fiber sensors.Through the preform-tofiber manufacturing technique,a variety of fiber sensors with complex functionalities spanning from the nanoscale to kilometer scale can be automated in a short time.Examples include temperature,acoustic,mechanical,chemical,biological,optoelectronic,and multifunctional sensors,which operate on diverse sensing principles such as resistance,capacitance,piezoelectricity,triboelectricity,photoelectricity,and thermoelectricity.This review outlines the principles of the thermal drawing process and provides a detailed overview of the latest advancements in various thermally drawn fiber sensors.Finally,the future developments of thermally drawn fiber sensors are discussed.展开更多
Tactile sensing of subcutaneous organ vibrations provides a promising route toward human-machine interfaces and wear-able diagnostics,particularly for voice rehabilitation and silent-speech communication.Here,we prese...Tactile sensing of subcutaneous organ vibrations provides a promising route toward human-machine interfaces and wear-able diagnostics,particularly for voice rehabilitation and silent-speech communication.Here,we present a bioinspired piezoelectric vibration sensor that mimics the graded stiffness and stress-based transduction mechanism of otolithic cilia in the human vestibular system.The device consists of a trapezoidal cantilever array with tip inertial masses,fabricated through a hybrid stereolithography 3D printing and laser micromachining process for rapid prototyping without cleanroom facilities.Finite-element modeling and experimental measurements demonstrate a fundamental resonance near 1.2 kHz,a 5%flat-bandwidth of 350 Hz,and an in-band charge sensitivity of 3.17 pC/g.A wearable proof-of-concept test further verifies the sensor's ability to reproducibly distinguish phoneme-specific vibration patterns in both time and frequency domains.This work establishes a foundation for bioinspired tactile sensing front-ends in wearable voice interfaces and other intelligent diagnostic systems integrated with machine-learning algorithms.展开更多
Motor imbalance is a critical failure mode in rotating machinery,potentially causing severe equipment damage if undetected.Traditional vibration-based diagnostic methods rely on direct sensor contact,leading to instal...Motor imbalance is a critical failure mode in rotating machinery,potentially causing severe equipment damage if undetected.Traditional vibration-based diagnostic methods rely on direct sensor contact,leading to installation challenges and measurement artifacts that can compromise accuracy.This study presents a novel radar-based framework for non-contact motor imbalance detection using 24 GHz continuous-wave radar.A dataset of 1802 experimental trials was sourced,covering four imbalance levels(0,10,20,30 g)across varying motor speeds(500–1500 rpm)and load torques(0–3 Nm).Dual-channel in-phase and quadrature radar signals were captured at 10,000 samples per second for 30-s intervals,preserving both amplitude and phase information for analysis.A multi-domain feature extraction methodology captured imbalance signatures in time,frequency,and complex signal domains.From 65 initial features,statistical analysis using Kruskal–Wallis tests identified significant descriptors,and recursive feature elimination with Random Forest reduced the feature set to 20 dimensions,achieving 69%dimensionality reduction without loss of performance.Six machine learning algorithms,Random Forest,Extra Trees Classifier,Extreme Gradient Boosting,Categorical Boosting,Support Vector Machine with radial basis function kernel,and k-Nearest Neighbors were evaluated with grid-search hyperparameter optimization and five-fold cross-validation.The Extra Trees Classifier achieved the best performance with 98.52%test accuracy,98%cross-validation accuracy,and minimal variance,maintaining per-class precision and recall above 97%.Its superior performance is attributed to its randomized split selection and full bootstrapping strategy,which reduce variance and overfitting while effectively capturing the nonlinear feature interactions and non-normal distributions present in the dataset.The model’s average inference time of 70 ms enables near real-time deployment.Comparative analysis demonstrates that the radar-based framework matches or exceeds traditional contact-based methods while eliminating their inherent limitations,providing a robust,scalable,and noninvasive solution for industrial motor condition monitoring,particularly in hazardous or space-constrained environments.展开更多
Climate change,natural disasters,pollution,and fast urbanization have made environmental security a more serious international issue.Timely,accurate,and multi-dimensional information is essential in the effective moni...Climate change,natural disasters,pollution,and fast urbanization have made environmental security a more serious international issue.Timely,accurate,and multi-dimensional information is essential in the effective monitoring and management of such complex challenges in the environment.The Earth Observation(EO)systems,including optical sensors,radar sensors,Light Detection and Ranging(LiDAR)sensors,thermal sensors,Unmanned Aerial Vehicle(UAV)sensors,and in-situ sensors,offer a good coverage of space and time,as well as provide useful information on land,water,and atmospheric processes.But the shortcomings or weaknesses of individual sensors,such as their vulnerability to weather conditions,spectral or spatial resolution,and gaps in time,can tend to limit their ability to provide a complete picture of the environment.One of the solutions has been multi-sensor fusion,which combines heterogeneous data and makes it more accurate,robust,and interpretable.This systematic review analyzes the latest methods of multi-sensor fusion,which are machine learning,deep learning,probabilistic models,and hybrid approaches,in terms of methodological principles,preprocessing needs,and computational frameworks.Applications in environmental security are highlighted,which include monitoring natural disasters,monitoring of climate and ecosystem,pollution monitoring,monitoring of land use change,and early warning systems.The review also covers evaluation measures,validation plans,and uncertainty measures,where a strict measure of evaluation is vital to making actionable decisions.Lastly,emerging issues,e.g.,data heterogeneity,computational needs,sensor interoperability,and prospects in the future,e.g.,AI-based adaptive fusion,UAVs and Internet of Things(IoT)integration,and scalable cloud-based systems,are discussed.The synthesis has highlighted the transformational capability of multi-sensor EO in terms of improving the environment in the context of environmental security and sustainable management.展开更多
The growing prevalence of exercise-induced tibial stress fractures demands wearable sensors capable of monitoring dynamic musculoskeletal loads with medical-grade precision.While flexible pressure-sensing insoles show...The growing prevalence of exercise-induced tibial stress fractures demands wearable sensors capable of monitoring dynamic musculoskeletal loads with medical-grade precision.While flexible pressure-sensing insoles show clinical potential,their development has been hindered by the intrinsic trade-off between high sensitivity and full-range linearity(R^(2)>0.99 up to 1 MPa)in conventional designs.Inspired by the tactile sensing mechanism of human skin,where dermal stratification enables wide-range pressure adaptation and ion-channelregulated signaling maintains linear electrical responses,we developed a dual-mechanism flexible iontronic pressure sensor(FIPS).This innovative design synergistically combines two bioinspired components:interdigitated fabric microstructures enabling pressure-proportional contact area expansion(αP1/3)and iontronic film facilitating self-adaptive ion concentration modulation(αP^(2/3)),which together generate a linear capacitance-pressure response(CαP).The FIPS achieves breakthrough performance:242 kPa^(-1)sensitivity with 0.997linearity across 0-1 MPa,yielding a record linear sensing factor(LSF=242,000).The design is validated across various substrates and ionic materials,demonstrating its versatility.Finally,the FIPS-driven design enables a smart insole demonstrating 1.8%error in tibial load assessment during gait analysis,outperforming nonlinear counterparts(6.5%error)in early fracture-risk prediction.The biomimetic design framework establishes a universal approach for developing high-performance linear sensors,establishing generalized principles for medical-grade wearable devices.展开更多
Indeed,a range of systems in the environment requires timely,spatially explicit,and credible information to support its environmental decision-making,but no one observing system can give the complete and reliable meas...Indeed,a range of systems in the environment requires timely,spatially explicit,and credible information to support its environmental decision-making,but no one observing system can give the complete and reliable measures of the Earth system across scales.This review summarizes how the realization of the Compute the Planet is underway in the form of machine learning,remote sensing,and sensor data fusion to generate decision-ready environmental insights.We use the application-first approach,which considers remote sensing,in situ and Internet of Things(IoT)sensing,and physics-based models as complementary streams of evidence with similar strengths and failures.We look critically at how an integrated system can convert heterogeneous observations to action products across three high impact application areas:atmosphere and air quality,water–land–ecosystem dynamics,and hazards.Rapid-response situational awareness,ecosystem condition metrics,drought and flood indicators,exposure maps,and hazard/extreme indicators are key products.The integrated systems to environment interface in three high impact application areas:atmosphere and air quality,water-land-ecosystem dynamics,and hazard Examine Our operational requirements can often determine real-life value such as latency,time stability,smooth degradation in the presence of missing or degraded inputs,and calibrated uncertainty usable in thresholdbased decisions.These pitfalls are common across fields:mismatch in the scale between a point sensor and a gridded product,objectives on proxies in remotely sensed measurements,domain shift in the extremes and changing baselines,and evaluation aspects,which overestimate generalization because of spatiotemporal autocorrelation.Based on these lessons,we present cross-domain proposals for strong validation,uncertainty quantification,provenance,and versioning,as well as fair performance evaluation.We conclude that the next era of environmental intelligence will see a reduction in average accuracy improvement and an increase in terms of robustness,transparency,and operational responsibility,thus allowing the integrated environmental intelligence system to be deployed,which may be relied on to monitor human health,resource allocation,and survival in a more climate-adapted world.展开更多
Fiber-optic sensing technology has the advantages of passivity, anti-electromagnetic interference, longdistancemeasurement, high sensitivity and high accuracy, small size, and adaptability to harsh environments such a...Fiber-optic sensing technology has the advantages of passivity, anti-electromagnetic interference, longdistancemeasurement, high sensitivity and high accuracy, small size, and adaptability to harsh environments such ashigh-vacuum, high-pressure, and strong magnetic fields compared with the traditional electrical sensing technology.However, with the increasing application requirements, how to further improve the sensitivity of fiber-optic sensors,extend the detection limit and improve the maintenance-free capability has become one of the core issues of thecurrent research. This paper reviews the principle, preparation, and application of fiber-optic microstructured sensingbased on abrupt field type. It specifically outlines the development and applications of micro-nano optical fibers,photonic crystal optical fibers, optical fiber gratings and structured optical fibers, and lists the main preparationmethods of two types of micro-nano optical fibers from the basic theory of optical fiber microstructured sensordevices.展开更多
The porous NiO nanoplates modified with rGO nanosheets and SnO_(2)nanoparticles are developed for accurate and rapid ppb-level NO_(2)detection.The developed SnO_(2)/NiO/rGO sensor towards 50 ppm NO_(2)gas demonstrates...The porous NiO nanoplates modified with rGO nanosheets and SnO_(2)nanoparticles are developed for accurate and rapid ppb-level NO_(2)detection.The developed SnO_(2)/NiO/rGO sensor towards 50 ppm NO_(2)gas demonstrates an excellent gas-sensing response of 14.8 at 23℃,which is 3.03 times that of Ni O/rGO sensor(4.89)and 6.49 times that of NiO sensor(2.28),respectively.The developed SnO_(2)/NiO/rGO sensor exhibits faster response/recovery speed(12.7/32.8 s@5 ppm),with extra-low theoretical detection limit of 0.15 ppb at room temperature.More fascinatingly,our sensors indicate great sensitivity,outstanding repeatability and long-term stability for longer than 7 weeks.Additionally,it also suggests that 1℃and 1%relative humidity have the same effect on the SnO_(2)/NiO/rGO sensor signal as approximately 13 ppb and 7.0 ppb NO_(2)gas change,respectively.Such excellent properties are mainly attributed to the large surface-to-volume ratio,which provides active sites to NO_(2)gas spread,adsorption and diffusion on material surface in redox reaction.Moreover,the ternary heterojunctions formed by NiO,rGO and SnO_(2)may serve as highly conductive channels to accelerate carrier transfer and abundant oxygen vacancies to reduce the adsorption energy for O_(2)and NO_(2)gas,thus further improving performance of the sensors.展开更多
In this study,using 3,5‑di(3′,5′‑dicarboxylphenyl)‑1H‑1,2,4‑triazole(H4L)as ligands,a gadolinia‑based organic framework complex{[GdNa(L)(H_(2)O)3]·2H_(2)O}_(n)(Gd‑Na‑MOF)was successfully designed and synthesize...In this study,using 3,5‑di(3′,5′‑dicarboxylphenyl)‑1H‑1,2,4‑triazole(H4L)as ligands,a gadolinia‑based organic framework complex{[GdNa(L)(H_(2)O)3]·2H_(2)O}_(n)(Gd‑Na‑MOF)was successfully designed and synthesized by hydrothermal method.The structure and properties were systematically characterized and tested by techniques such as single‑crystal X‑ray diffraction,powder X‑ray diffraction,thermogravimetric analysis,infrared spectroscopy,and fluorescence spectroscopy.The results indicate that this complex has a unique 3D structure,excellent thermal stability,and outstanding luminescent performance.Based on its luminescent properties,a polymer‑embedding method was employed to fabricate the Gd‑Na‑MOF into a flexible,washable composite fluorescent film,Gd‑Na‑MOF@PMMA/BMA(PMMA=polymethyl methacrylate,BMA=butyl methacrylate).This fluorescent film exhibited highly sensitive recognition capability for tyramine,with a low detection limit of 1.66μmol·L^(-1).It was used for the detection of tyramine in bananas,with a recovery rate of 96.92%‑100.26%.CCDC:2466949.展开更多
Based on 4'-(1H-tetrazol-5-yl)-[1,1'-biphenyl]-2,4,6-tricarboxylic acid(H_(4)bta)ligand,zinc metal-organic framework(Zn-MOF):{[Zn_(2)(bta)(bpy)_(2)(H_(2)O)]·1.5H_(2)O}_(n)(bpy=2,2'-bipyridine)was desi...Based on 4'-(1H-tetrazol-5-yl)-[1,1'-biphenyl]-2,4,6-tricarboxylic acid(H_(4)bta)ligand,zinc metal-organic framework(Zn-MOF):{[Zn_(2)(bta)(bpy)_(2)(H_(2)O)]·1.5H_(2)O}_(n)(bpy=2,2'-bipyridine)was designed and synthesized by hydrothermal method.Its structure was characterized by elemental analysis,IR spectra,X-ray single crystal diffraction,etc.The asymmetric unit of Zn-MOF contains two crystallographically independent Zn^(2+)ions.Through the connection of Zn^(2+)ions via H_(4)bta,a 1D double-layer network structure is formed.Adjacent double-layer networks further form a 2D supramolecular network through hydrogen bonding.Notably,Zn-MOF exhibited excellent fluorescence properties and could efficiently and sensitively detect various water pollutants:4-nitrophenol(4-NP),Cu^(2+),and pyrimethanil(Pth).Additionally,the mechanism of fluorescence sensing was investigated.CCDC:2432230.展开更多
Sleep monitoring is an important part of health management because sleep quality is crucial for restoration of human health.However,current commercial products of polysomnography are cumbersome with connecting wires a...Sleep monitoring is an important part of health management because sleep quality is crucial for restoration of human health.However,current commercial products of polysomnography are cumbersome with connecting wires and state-of-the-art flexible sensors are still interferential for being attached to the body.Herein,we develop a flexible-integrated multimodal sensing patch based on hydrogel and its application in unconstraint sleep monitoring.The patch comprises a bottom hydrogel-based dualmode pressure–temperature sensing layer and a top electrospun nanofiber-based non-contact detection layer as one integrated device.The hydrogel as core substrate exhibits strong toughness and water retention,and the multimodal sensing of temperature,pressure,and non-contact proximity is realized based on different sensing mechanisms with no crosstalk interference.The multimodal sensing function is verified in a simulated real-world scenario by a robotic hand grasping objects to validate its practicability.Multiple multimodal sensing patches integrated on different locations of a pillow are assembled for intelligent sleep monitoring.Versatile human–pillow interaction information as well as their evolution over time are acquired and analyzed by a one-dimensional convolutional neural network.Track of head movement and recognition of bad patterns that may lead to poor sleep are achieved,which provides a promising approach for sleep monitoring.展开更多
This review summarizes studies of hydrothermal alteration minerals at the Qiucun gold deposit in southeastern China and focuses on characterization and mapping of the deposit using hyperspectral remote sensing.The dep...This review summarizes studies of hydrothermal alteration minerals at the Qiucun gold deposit in southeastern China and focuses on characterization and mapping of the deposit using hyperspectral remote sensing.The deposit exhibits multistage fluid-rock interaction,as evidenced by systematic alteration assemblages,including silicification,sericitization by white micas,the development of argillaceous clays,variable chloritization,and locally significant carbonate alteration.We describe the genetic importance of such mineral groups and emphasize their diagnostic Visible and Near-Infrared to Short-Wave Infrared(VNIR-SWIR)spectral signatures,especially Al-OH,Mg-OH/Fe-OH,and CO3 absorption bands,which make it possible to distinguish between minerals,not to mention the fact that,in some instances,compositional trends may be predicted.This review’s methodological advances are discussed beginning with data collection at satellite,airborne,and ground levels,proceeding to processing procedures,such as atmospheric and topographic correction,and culminating in spectral analysis,including continuum removal,spectral matching,and unmixing/classification techniques.An integrated study of hyperspectral findings reveals that alteration minerals develop spatially coherent zones that are strongly controlled by fault/fracture structures and host-rock reactivity,producing proximal silicification/sericitization cores and larger silicified/larcenies of argillaceous rocks owing to diverse apex coverings of carbonate.This should be combined with petrography and geochemistry to address overprinting,mixed pixels,and surface weathering,and to couple mineral maps with ore-forming processes.The review finds that hyperspectral remote sensing offers a solid modeling platform for the deposit-scale alteration at Qiucun and other hydrothermal gold systems,and outlines the directions for future research to integrate quantitatively and more threedimensional alteration characterization.展开更多
Azobenzene-winged phenanthrolines(L1 and L2)were designed,synthesized,and fully characterized.Ligand L1 forms an in-situ cobalt complex,which has been effectively employed as a circular dichroism(CD)-active chiral sen...Azobenzene-winged phenanthrolines(L1 and L2)were designed,synthesized,and fully characterized.Ligand L1 forms an in-situ cobalt complex,which has been effectively employed as a circular dichroism(CD)-active chiral sensor.The resulting ternary complex(L1-Co^(2+)-amino alcohol)exhibits pronounced exciton-coupled circular dichroism(ECCD)signals at the characteristic azobenzene absorption bands.These signals arise from efficient chirality transfer from the chiral amino alcohol to the azobenzene chromophores,enabling the determination of the absolute configuration of chiral amino alcohols.Accordingly,the L1-Co^(2+)coordination system demonstrates considerably potential in chirality sensing applications.Remarkably,the induced ECCD signals are highly responsive to multiple external stimuli,including photoirradiation,solvent polarity,temperature,and redox conditions.In particular,temperature and redox changes can induce a reversible inversion of the ECCD signal,thereby establishing this system as a multifunctional,stimuli-responsive chiroptical molecular switch.展开更多
The sensitivity and quantification capability of surface-enhanced Raman scattering(SERS)substrates are mutually exclusive,because the ultrasensitive SERS sites(hottest spots)necessary for the sensitivity will signific...The sensitivity and quantification capability of surface-enhanced Raman scattering(SERS)substrates are mutually exclusive,because the ultrasensitive SERS sites(hottest spots)necessary for the sensitivity will significantly magnify the SERS signals of the analyte molecules and thus each of these molecules will be miscounted to be hundreds during the quantification process.We demonstrate a concept to circumvent the above contradiction by engineering a timeshare SERS platform capable of working at the quantitative or the sensitive mode on demand.The timeshare SERS platform was constructed by transferring a monolayer gold nanosphere film onto elastic substrates(e.g.,hydrogel).The volume change of the hydrogel could adjust the inter-nanosphere distance,dynamically controlling the formation or extinction of the SERS hottest spots on the same SERS substrate without influencing the spatial distribution of the analyte molecules.The timeshare SERS platform without the SERS hottest spots showed strong quantification capability,while when equipped with a substantial number of the SERS hottest spots exhibited ultrahigh sensitivity.We demonstrated quantitative and ultrasensitive detection of various analyte molecules using the quantitative and the sensitive mode of the timeshare SERS platform,respectively.We opened an avenue towards designing SERS substrates with both high sensitivity and strong quantification capability.展开更多
Interferometry is a crucial investigative technique used across diverse fields to achieve highprecision measurements.It works by analyzing the phase difference between two interfering waves,which results from variatio...Interferometry is a crucial investigative technique used across diverse fields to achieve highprecision measurements.It works by analyzing the phase difference between two interfering waves,which results from variations in optical path lengths within an interferometer.We introduce a novel method for directly measuring changes in the phase difference within an optical interferometer,importantly,with the added advantage of a controllable enhancement factor.This approach is achieved through a two-step process:first,the optical phase difference is encoded into a sub-GHz radiofrequency(RF)signal using microwave-photonic manipulation;then,RF interferometry-assisted phase amplification is implemented at the destructive interference point.In our experiments,we demonstrate a phase sensitivity of 2.14 rad∕nm operating at 140 MHz using a miniature in-fiber Fabry-Pérot interferometer for sub-nanometer displacement sensing,which reveals a sensitivity magnification factor of 258.6.With further refinement,we anticipate that even higher enhancement factors can be achieved,paving the way for the development of cost-effective,ultrasensitive interferometry-based instruments for high-precision optical measurements.展开更多
The demand for sensors capable of operating in extreme environment of the fields,such as aerospace vehicles,aeroengines and fire protection,is rapidly increasing.However,developing flexible ceramic fibrous pressure se...The demand for sensors capable of operating in extreme environment of the fields,such as aerospace vehicles,aeroengines and fire protection,is rapidly increasing.However,developing flexible ceramic fibrous pressure sensors that combine high temperature stability with robust mechanical properties remains a significant challenge.Herein,through precise multi-scale process control,high-strength(2.1 MPa)TiC-SiC flexible fibrous membrane is successfully fabricated.The membrane exhibits exceptional thermal resistance(2000℃)and long–term thermal stability(1800℃ for 5 h)in the inert atmosphere.Meanwhile,the TiC-SiC fibrous membrane shows excellent oxidation resistance and still achieves strength of 1.8 MPa after being oxidized at 1200℃ for 1 h in air.Remarkably,TiC-SiC fibrous membrane withstands a load of approximately 1400 times its own weight and the ablation of butane flame(~1300℃)for at least 1 h without breaking.Notably,after heat treatment at 1800℃ for 5 h in an argon atmosphere,the TiC-SiC fibrous membrane even sustains pressure–sensing performance for up to 300 cycles.The membrane exhibits stable resistivity up to 900℃ and shows sensing stability under butane flame.The results of this work provide an effective and feasible solution to fill the research gap of flexible fibrous sensors for extreme environments.展开更多
Background Zearalenone(ZEN),a common mycotoxin in ruminant diets,could disturb the rumen ecosystem and impair rumen fermentation.Noticeably,ZEN has been shown to reduce the relative abundances of specific bacterial ta...Background Zearalenone(ZEN),a common mycotoxin in ruminant diets,could disturb the rumen ecosystem and impair rumen fermentation.Noticeably,ZEN has been shown to reduce the relative abundances of specific bacterial taxa that potentially possess quorum sensing(QS)functions,which are deemed essential for the microbial interactions and adaptations during rumen fermentation.Nonetheless,whether QS communications participate in the responses of rumen microbial fermentation to ZEN remains unknown.Therefore,the present trial was performed to explore the potential roles of QS during the alterations of rumen microbial fermentation by ZEN through a rumen simulation technique(RUSITEC)system,in a replicated 4×4 Latin square design.Results ZEN significantly(P<0.05)reduced QS signal autoinducer-2(AI-2),and tended to(P=0.051)downregulate QS signal C4-homoserine lactone(HSL).ZEN also significantly(P<0.05)decreased total volatile fatty acid(TVFA),acetate,propionate,isobutyrate,isovalerate,organic matter disappearance(OMD),neutral detergent fiber disappearance(NDFD),and acid detergent fiber disappearance(ADFD)in different manners.The linear discriminant analysis effect size(LEf Se)analysis indicated significantly(P<0.05)differential enrichments of a series of bacterial taxa such as Butyrivibrio_sp_X503,Rhizobium daejeonense,Hoylesella buccalis,Ezakiella coagulans,Enterococcus cecorum,Ruminococcus_sp_zg-924,Polystyrenella longa,and Methylacidimicrobium fagopyrum across different treatments.The phylogenetic investigation of communities by reconstruction of unobserved states 2(PICRUSt2)analysis suggested that QS were predicted to be significantly(P<0.05)affected by ZEN.The metabolomics analysis detected considerable significantly(P<0.05)differing metabolites and implied that ZEN challenge significantly(P<0.05)influenced the indole alkaloid biosynthesis,biosynthesis of alkaloids derived from shikimate pathway,and sesquiterpenoid and triterpenoid biosynthesis.Significant(P<0.05)interconnections of QS molecules with the differential rumen fermentation traits,differential bacterial taxa,and differential metabolites were exhibited by Spearman analysis.Conclusions ZEN negatively affected the QS signals of AI-2 and C4-HSL,which was found to correlate with the fluctuations in specific rumen fermentation characteristics,ruminal bacterial populations,and ruminal metabolisms.These interrelationships implied the potential involvement of QS in the reactions of rumen microbiota to ZEN contamination,and probably contributed to the inhibition of rumen fermentation.展开更多
Accurate and efficient detection of building changes in remote sensing imagery is crucial for urban planning,disaster emergency response,and resource management.However,existing methods face challenges such as spectra...Accurate and efficient detection of building changes in remote sensing imagery is crucial for urban planning,disaster emergency response,and resource management.However,existing methods face challenges such as spectral similarity between buildings and backgrounds,sensor variations,and insufficient computational efficiency.To address these challenges,this paper proposes a novel Multi-scale Efficient Wavelet-based Change Detection Network(MewCDNet),which integrates the advantages of Convolutional Neural Networks and Transformers,balances computational costs,and achieves high-performance building change detection.The network employs EfficientNet-B4 as the backbone for hierarchical feature extraction,integrates multi-level feature maps through a multi-scale fusion strategy,and incorporates two key modules:Cross-temporal Difference Detection(CTDD)and Cross-scale Wavelet Refinement(CSWR).CTDD adopts a dual-branch architecture that combines pixel-wise differencing with semanticaware Euclidean distance weighting to enhance the distinction between true changes and background noise.CSWR integrates Haar-based Discrete Wavelet Transform with multi-head cross-attention mechanisms,enabling cross-scale feature fusion while significantly improving edge localization and suppressing spurious changes.Extensive experiments on four benchmark datasets demonstrate MewCDNet’s superiority over comparison methods:achieving F1 scores of 91.54%on LEVIR,93.70%on WHUCD,and 64.96%on S2Looking for building change detection.Furthermore,MewCDNet exhibits optimal performance on the multi-class⋅SYSU dataset(F1:82.71%),highlighting its exceptional generalization capability.展开更多
Shallow landslides are strongly controlled by near-surface lithological variability,yet conventional geological maps are often too generalized to support accurate susceptibility assessment in complex terrains.This rev...Shallow landslides are strongly controlled by near-surface lithological variability,yet conventional geological maps are often too generalized to support accurate susceptibility assessment in complex terrains.This review synthesizes recent advances in remote sensing–based lithological mapping and evaluates their integration into landslide susceptibility modeling.Evidence from the literature indicates that remote sensing-derived lithological products,particularly those incorporating mineralogical information and higher spatial resolution,consistently outperform traditional geological maps in improving model accuracy and spatial detail,especially in heterogeneous environments.However,key challenges remain,including scale mismatches between surface observations and subsurface controls,limited ground validation,uncertainty propagation,and restricted model transferability across regions.The review identifies multi-sensor data fusion and explainable machine learning as the most promising directions for advancing lithological discrimination and model reliability.Future progress depends on integrating remote sensing with process-based understanding,improving validation strategies,and standardizing uncertainty reporting.These developments are essential for enabling more robust,scalable,and operationally relevant landslide susceptibility assessments in complex terrains.Lastly,we describe the directions of research that focus on multi-sensor fusion,explainable machine learning,UAV(Unmanned Aerial Vehicle)-enabled validation,and standardized uncertainty reporting that can help articulate landslide susceptibility assessment,making them even more robust and operationally significant.展开更多
As a vital food crop,rice is an important part of global food crops.Studying the spatiotemporal changes in rice cultivation facilitates early prediction of production risks and provides support for agricultural policy...As a vital food crop,rice is an important part of global food crops.Studying the spatiotemporal changes in rice cultivation facilitates early prediction of production risks and provides support for agricultural policy decisions related to rice.With the increasing application of satellite remote sensing technology in crop monitoring,remote sensing for rice cultivation has emerged as a novel approach,offering new perspectives for monitoring rice planting.This paper briefly outlined the current research and development status of satellite remote sensing for monitoring rice cultivation both at home and abroad.Foreign scholars have made innovations in data sources and methodologies for satellite remote sensing monitoring,and utilized multi-source satellite information and machine learning algorithms to enhance the accuracy of rice planting monitoring.Scholars in China have achieved significant results in the study of satellite remote sensing for monitoring rice cultivation.Their research and application in monitoring rice planting areas provide valuable references for agricultural production management.However,satellite remote sensing monitoring of rice still faces challenges such as low spatiotemporal resolution and difficulties related to cloud cover and data fusion,which require further in-depth investigation.Additionally,there are shortcomings in the accuracy of remote sensing monitoring for fragmented farmland plots and smallholder farming.To address these issues,future efforts should focus on developing multi-source heterogeneous data fusion analysis technologies and researching monitoring systems.These advancements are expected to enable high-precision large-scale acquisition of rice planting information,laying a foundation for future smart agriculture.展开更多
基金supported by the National Key Research and Development Program of China(2023YFB3809800)the National Natural Science Foundation of China(52172249,52525601)+2 种基金the Chinese Academy of Sciences Talents Program(E2290701)the Jiangsu Province Talents Program(JSSCRC2023545)the Special Fund Project of Carbon Peaking Carbon Neutrality Science and Technology Innovation of Jiangsu Province(BE2022011).
文摘Flexible fiber sensors,However,traditional methods face challenges in fabricating low-cost,large-scale fiber sensors.In recent years,the thermal drawing process has rapidly advanced,offering a novel approach to flexible fiber sensors.Through the preform-tofiber manufacturing technique,a variety of fiber sensors with complex functionalities spanning from the nanoscale to kilometer scale can be automated in a short time.Examples include temperature,acoustic,mechanical,chemical,biological,optoelectronic,and multifunctional sensors,which operate on diverse sensing principles such as resistance,capacitance,piezoelectricity,triboelectricity,photoelectricity,and thermoelectricity.This review outlines the principles of the thermal drawing process and provides a detailed overview of the latest advancements in various thermally drawn fiber sensors.Finally,the future developments of thermally drawn fiber sensors are discussed.
文摘Tactile sensing of subcutaneous organ vibrations provides a promising route toward human-machine interfaces and wear-able diagnostics,particularly for voice rehabilitation and silent-speech communication.Here,we present a bioinspired piezoelectric vibration sensor that mimics the graded stiffness and stress-based transduction mechanism of otolithic cilia in the human vestibular system.The device consists of a trapezoidal cantilever array with tip inertial masses,fabricated through a hybrid stereolithography 3D printing and laser micromachining process for rapid prototyping without cleanroom facilities.Finite-element modeling and experimental measurements demonstrate a fundamental resonance near 1.2 kHz,a 5%flat-bandwidth of 350 Hz,and an in-band charge sensitivity of 3.17 pC/g.A wearable proof-of-concept test further verifies the sensor's ability to reproducibly distinguish phoneme-specific vibration patterns in both time and frequency domains.This work establishes a foundation for bioinspired tactile sensing front-ends in wearable voice interfaces and other intelligent diagnostic systems integrated with machine-learning algorithms.
基金funded by Princess Nourah bint Abdulrahman University Researchers Support-ing Project number(PNURSP2026R346)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Motor imbalance is a critical failure mode in rotating machinery,potentially causing severe equipment damage if undetected.Traditional vibration-based diagnostic methods rely on direct sensor contact,leading to installation challenges and measurement artifacts that can compromise accuracy.This study presents a novel radar-based framework for non-contact motor imbalance detection using 24 GHz continuous-wave radar.A dataset of 1802 experimental trials was sourced,covering four imbalance levels(0,10,20,30 g)across varying motor speeds(500–1500 rpm)and load torques(0–3 Nm).Dual-channel in-phase and quadrature radar signals were captured at 10,000 samples per second for 30-s intervals,preserving both amplitude and phase information for analysis.A multi-domain feature extraction methodology captured imbalance signatures in time,frequency,and complex signal domains.From 65 initial features,statistical analysis using Kruskal–Wallis tests identified significant descriptors,and recursive feature elimination with Random Forest reduced the feature set to 20 dimensions,achieving 69%dimensionality reduction without loss of performance.Six machine learning algorithms,Random Forest,Extra Trees Classifier,Extreme Gradient Boosting,Categorical Boosting,Support Vector Machine with radial basis function kernel,and k-Nearest Neighbors were evaluated with grid-search hyperparameter optimization and five-fold cross-validation.The Extra Trees Classifier achieved the best performance with 98.52%test accuracy,98%cross-validation accuracy,and minimal variance,maintaining per-class precision and recall above 97%.Its superior performance is attributed to its randomized split selection and full bootstrapping strategy,which reduce variance and overfitting while effectively capturing the nonlinear feature interactions and non-normal distributions present in the dataset.The model’s average inference time of 70 ms enables near real-time deployment.Comparative analysis demonstrates that the radar-based framework matches or exceeds traditional contact-based methods while eliminating their inherent limitations,providing a robust,scalable,and noninvasive solution for industrial motor condition monitoring,particularly in hazardous or space-constrained environments.
文摘Climate change,natural disasters,pollution,and fast urbanization have made environmental security a more serious international issue.Timely,accurate,and multi-dimensional information is essential in the effective monitoring and management of such complex challenges in the environment.The Earth Observation(EO)systems,including optical sensors,radar sensors,Light Detection and Ranging(LiDAR)sensors,thermal sensors,Unmanned Aerial Vehicle(UAV)sensors,and in-situ sensors,offer a good coverage of space and time,as well as provide useful information on land,water,and atmospheric processes.But the shortcomings or weaknesses of individual sensors,such as their vulnerability to weather conditions,spectral or spatial resolution,and gaps in time,can tend to limit their ability to provide a complete picture of the environment.One of the solutions has been multi-sensor fusion,which combines heterogeneous data and makes it more accurate,robust,and interpretable.This systematic review analyzes the latest methods of multi-sensor fusion,which are machine learning,deep learning,probabilistic models,and hybrid approaches,in terms of methodological principles,preprocessing needs,and computational frameworks.Applications in environmental security are highlighted,which include monitoring natural disasters,monitoring of climate and ecosystem,pollution monitoring,monitoring of land use change,and early warning systems.The review also covers evaluation measures,validation plans,and uncertainty measures,where a strict measure of evaluation is vital to making actionable decisions.Lastly,emerging issues,e.g.,data heterogeneity,computational needs,sensor interoperability,and prospects in the future,e.g.,AI-based adaptive fusion,UAVs and Internet of Things(IoT)integration,and scalable cloud-based systems,are discussed.The synthesis has highlighted the transformational capability of multi-sensor EO in terms of improving the environment in the context of environmental security and sustainable management.
基金supported by the National Natural Science Foundation of China(NSFC 52175281,52475315)Youth Innovation Promotion Association of CAS(2021382)。
文摘The growing prevalence of exercise-induced tibial stress fractures demands wearable sensors capable of monitoring dynamic musculoskeletal loads with medical-grade precision.While flexible pressure-sensing insoles show clinical potential,their development has been hindered by the intrinsic trade-off between high sensitivity and full-range linearity(R^(2)>0.99 up to 1 MPa)in conventional designs.Inspired by the tactile sensing mechanism of human skin,where dermal stratification enables wide-range pressure adaptation and ion-channelregulated signaling maintains linear electrical responses,we developed a dual-mechanism flexible iontronic pressure sensor(FIPS).This innovative design synergistically combines two bioinspired components:interdigitated fabric microstructures enabling pressure-proportional contact area expansion(αP1/3)and iontronic film facilitating self-adaptive ion concentration modulation(αP^(2/3)),which together generate a linear capacitance-pressure response(CαP).The FIPS achieves breakthrough performance:242 kPa^(-1)sensitivity with 0.997linearity across 0-1 MPa,yielding a record linear sensing factor(LSF=242,000).The design is validated across various substrates and ionic materials,demonstrating its versatility.Finally,the FIPS-driven design enables a smart insole demonstrating 1.8%error in tibial load assessment during gait analysis,outperforming nonlinear counterparts(6.5%error)in early fracture-risk prediction.The biomimetic design framework establishes a universal approach for developing high-performance linear sensors,establishing generalized principles for medical-grade wearable devices.
文摘Indeed,a range of systems in the environment requires timely,spatially explicit,and credible information to support its environmental decision-making,but no one observing system can give the complete and reliable measures of the Earth system across scales.This review summarizes how the realization of the Compute the Planet is underway in the form of machine learning,remote sensing,and sensor data fusion to generate decision-ready environmental insights.We use the application-first approach,which considers remote sensing,in situ and Internet of Things(IoT)sensing,and physics-based models as complementary streams of evidence with similar strengths and failures.We look critically at how an integrated system can convert heterogeneous observations to action products across three high impact application areas:atmosphere and air quality,water–land–ecosystem dynamics,and hazards.Rapid-response situational awareness,ecosystem condition metrics,drought and flood indicators,exposure maps,and hazard/extreme indicators are key products.The integrated systems to environment interface in three high impact application areas:atmosphere and air quality,water-land-ecosystem dynamics,and hazard Examine Our operational requirements can often determine real-life value such as latency,time stability,smooth degradation in the presence of missing or degraded inputs,and calibrated uncertainty usable in thresholdbased decisions.These pitfalls are common across fields:mismatch in the scale between a point sensor and a gridded product,objectives on proxies in remotely sensed measurements,domain shift in the extremes and changing baselines,and evaluation aspects,which overestimate generalization because of spatiotemporal autocorrelation.Based on these lessons,we present cross-domain proposals for strong validation,uncertainty quantification,provenance,and versioning,as well as fair performance evaluation.We conclude that the next era of environmental intelligence will see a reduction in average accuracy improvement and an increase in terms of robustness,transparency,and operational responsibility,thus allowing the integrated environmental intelligence system to be deployed,which may be relied on to monitor human health,resource allocation,and survival in a more climate-adapted world.
基金support by National Natural Science Foundation of China (Nos. 51606158, 12104402)
文摘Fiber-optic sensing technology has the advantages of passivity, anti-electromagnetic interference, longdistancemeasurement, high sensitivity and high accuracy, small size, and adaptability to harsh environments such ashigh-vacuum, high-pressure, and strong magnetic fields compared with the traditional electrical sensing technology.However, with the increasing application requirements, how to further improve the sensitivity of fiber-optic sensors,extend the detection limit and improve the maintenance-free capability has become one of the core issues of thecurrent research. This paper reviews the principle, preparation, and application of fiber-optic microstructured sensingbased on abrupt field type. It specifically outlines the development and applications of micro-nano optical fibers,photonic crystal optical fibers, optical fiber gratings and structured optical fibers, and lists the main preparationmethods of two types of micro-nano optical fibers from the basic theory of optical fiber microstructured sensordevices.
基金funded by the National Natural Science Foundation of China(No.62364002)Key Scientific Research Projects of Universities in Henan Province(No.24A510014)+5 种基金Xinjiang-Changji Vocational Education Alliance Special Project(No.2050305)National Laboratory of Solid State Microstructures,Nanjing University(No.M36001)Jiangsu Key Laboratory of Optoelectronic Information Functional Materials,Nanjing University(No.ndgd2024005)Henan Province Higher Education College Student Innovation Training Program Project(No.202410478019)the Doctoral Research Initiation Fund Project,Zhoukou Normal University(No.ZKNUC2022018)the Natural Science Foundation Project of Xinjiang Uygur Autonomous Region(No.2022D01C006)。
文摘The porous NiO nanoplates modified with rGO nanosheets and SnO_(2)nanoparticles are developed for accurate and rapid ppb-level NO_(2)detection.The developed SnO_(2)/NiO/rGO sensor towards 50 ppm NO_(2)gas demonstrates an excellent gas-sensing response of 14.8 at 23℃,which is 3.03 times that of Ni O/rGO sensor(4.89)and 6.49 times that of NiO sensor(2.28),respectively.The developed SnO_(2)/NiO/rGO sensor exhibits faster response/recovery speed(12.7/32.8 s@5 ppm),with extra-low theoretical detection limit of 0.15 ppb at room temperature.More fascinatingly,our sensors indicate great sensitivity,outstanding repeatability and long-term stability for longer than 7 weeks.Additionally,it also suggests that 1℃and 1%relative humidity have the same effect on the SnO_(2)/NiO/rGO sensor signal as approximately 13 ppb and 7.0 ppb NO_(2)gas change,respectively.Such excellent properties are mainly attributed to the large surface-to-volume ratio,which provides active sites to NO_(2)gas spread,adsorption and diffusion on material surface in redox reaction.Moreover,the ternary heterojunctions formed by NiO,rGO and SnO_(2)may serve as highly conductive channels to accelerate carrier transfer and abundant oxygen vacancies to reduce the adsorption energy for O_(2)and NO_(2)gas,thus further improving performance of the sensors.
文摘In this study,using 3,5‑di(3′,5′‑dicarboxylphenyl)‑1H‑1,2,4‑triazole(H4L)as ligands,a gadolinia‑based organic framework complex{[GdNa(L)(H_(2)O)3]·2H_(2)O}_(n)(Gd‑Na‑MOF)was successfully designed and synthesized by hydrothermal method.The structure and properties were systematically characterized and tested by techniques such as single‑crystal X‑ray diffraction,powder X‑ray diffraction,thermogravimetric analysis,infrared spectroscopy,and fluorescence spectroscopy.The results indicate that this complex has a unique 3D structure,excellent thermal stability,and outstanding luminescent performance.Based on its luminescent properties,a polymer‑embedding method was employed to fabricate the Gd‑Na‑MOF into a flexible,washable composite fluorescent film,Gd‑Na‑MOF@PMMA/BMA(PMMA=polymethyl methacrylate,BMA=butyl methacrylate).This fluorescent film exhibited highly sensitive recognition capability for tyramine,with a low detection limit of 1.66μmol·L^(-1).It was used for the detection of tyramine in bananas,with a recovery rate of 96.92%‑100.26%.CCDC:2466949.
文摘Based on 4'-(1H-tetrazol-5-yl)-[1,1'-biphenyl]-2,4,6-tricarboxylic acid(H_(4)bta)ligand,zinc metal-organic framework(Zn-MOF):{[Zn_(2)(bta)(bpy)_(2)(H_(2)O)]·1.5H_(2)O}_(n)(bpy=2,2'-bipyridine)was designed and synthesized by hydrothermal method.Its structure was characterized by elemental analysis,IR spectra,X-ray single crystal diffraction,etc.The asymmetric unit of Zn-MOF contains two crystallographically independent Zn^(2+)ions.Through the connection of Zn^(2+)ions via H_(4)bta,a 1D double-layer network structure is formed.Adjacent double-layer networks further form a 2D supramolecular network through hydrogen bonding.Notably,Zn-MOF exhibited excellent fluorescence properties and could efficiently and sensitively detect various water pollutants:4-nitrophenol(4-NP),Cu^(2+),and pyrimethanil(Pth).Additionally,the mechanism of fluorescence sensing was investigated.CCDC:2432230.
基金supported by the National Key Research and Development Program of China under Grant(2024YFE0100400)Taishan Scholars Project Special Funds(tsqn202312035)+2 种基金the open research foundation of State Key Laboratory of Integrated Chips and Systems,the Tianjin Science and Technology Plan Project(No.22JCZDJC00630)the Higher Education Institution Science and Technology Research Project of Hebei Province(No.JZX2024024)Jinan City-University Integrated Development Strategy Project under Grant(JNSX2023017).
文摘Sleep monitoring is an important part of health management because sleep quality is crucial for restoration of human health.However,current commercial products of polysomnography are cumbersome with connecting wires and state-of-the-art flexible sensors are still interferential for being attached to the body.Herein,we develop a flexible-integrated multimodal sensing patch based on hydrogel and its application in unconstraint sleep monitoring.The patch comprises a bottom hydrogel-based dualmode pressure–temperature sensing layer and a top electrospun nanofiber-based non-contact detection layer as one integrated device.The hydrogel as core substrate exhibits strong toughness and water retention,and the multimodal sensing of temperature,pressure,and non-contact proximity is realized based on different sensing mechanisms with no crosstalk interference.The multimodal sensing function is verified in a simulated real-world scenario by a robotic hand grasping objects to validate its practicability.Multiple multimodal sensing patches integrated on different locations of a pillow are assembled for intelligent sleep monitoring.Versatile human–pillow interaction information as well as their evolution over time are acquired and analyzed by a one-dimensional convolutional neural network.Track of head movement and recognition of bad patterns that may lead to poor sleep are achieved,which provides a promising approach for sleep monitoring.
基金supported by the Jiangsu Province Frontier Leading Technology Basic Research Special Project-Research on the New Optoelectronic Imaging and Information Processing Basic Theory and Method(No:BK20192003).
文摘This review summarizes studies of hydrothermal alteration minerals at the Qiucun gold deposit in southeastern China and focuses on characterization and mapping of the deposit using hyperspectral remote sensing.The deposit exhibits multistage fluid-rock interaction,as evidenced by systematic alteration assemblages,including silicification,sericitization by white micas,the development of argillaceous clays,variable chloritization,and locally significant carbonate alteration.We describe the genetic importance of such mineral groups and emphasize their diagnostic Visible and Near-Infrared to Short-Wave Infrared(VNIR-SWIR)spectral signatures,especially Al-OH,Mg-OH/Fe-OH,and CO3 absorption bands,which make it possible to distinguish between minerals,not to mention the fact that,in some instances,compositional trends may be predicted.This review’s methodological advances are discussed beginning with data collection at satellite,airborne,and ground levels,proceeding to processing procedures,such as atmospheric and topographic correction,and culminating in spectral analysis,including continuum removal,spectral matching,and unmixing/classification techniques.An integrated study of hyperspectral findings reveals that alteration minerals develop spatially coherent zones that are strongly controlled by fault/fracture structures and host-rock reactivity,producing proximal silicification/sericitization cores and larger silicified/larcenies of argillaceous rocks owing to diverse apex coverings of carbonate.This should be combined with petrography and geochemistry to address overprinting,mixed pixels,and surface weathering,and to couple mineral maps with ore-forming processes.The review finds that hyperspectral remote sensing offers a solid modeling platform for the deposit-scale alteration at Qiucun and other hydrothermal gold systems,and outlines the directions for future research to integrate quantitatively and more threedimensional alteration characterization.
基金the support of this work by the National Natural Science Foundation of China(Nos.22471182,22271201,22422108,22171194)the Science&Technology Department of Sichuan Province(No.2025ZNSFSC0125)+1 种基金the Fundamental Research Funds for the Central Universities(No.20826041D4117)the Comprehensive Training Platform of Specialized Laboratory,College of Chemistry.
文摘Azobenzene-winged phenanthrolines(L1 and L2)were designed,synthesized,and fully characterized.Ligand L1 forms an in-situ cobalt complex,which has been effectively employed as a circular dichroism(CD)-active chiral sensor.The resulting ternary complex(L1-Co^(2+)-amino alcohol)exhibits pronounced exciton-coupled circular dichroism(ECCD)signals at the characteristic azobenzene absorption bands.These signals arise from efficient chirality transfer from the chiral amino alcohol to the azobenzene chromophores,enabling the determination of the absolute configuration of chiral amino alcohols.Accordingly,the L1-Co^(2+)coordination system demonstrates considerably potential in chirality sensing applications.Remarkably,the induced ECCD signals are highly responsive to multiple external stimuli,including photoirradiation,solvent polarity,temperature,and redox conditions.In particular,temperature and redox changes can induce a reversible inversion of the ECCD signal,thereby establishing this system as a multifunctional,stimuli-responsive chiroptical molecular switch.
基金supported by the National Science Foundation of China(12304422,52501261,52273233)the China Postdoctoral Science Foundation(512200-X92103)+2 种基金the Natural Science Foundation of Jiangsu Province(BK20230911)the fundamental Research Funds for the Central Universities(30923010209)Natural Science Foundation of Inner Mongolia(2025QN05053).
文摘The sensitivity and quantification capability of surface-enhanced Raman scattering(SERS)substrates are mutually exclusive,because the ultrasensitive SERS sites(hottest spots)necessary for the sensitivity will significantly magnify the SERS signals of the analyte molecules and thus each of these molecules will be miscounted to be hundreds during the quantification process.We demonstrate a concept to circumvent the above contradiction by engineering a timeshare SERS platform capable of working at the quantitative or the sensitive mode on demand.The timeshare SERS platform was constructed by transferring a monolayer gold nanosphere film onto elastic substrates(e.g.,hydrogel).The volume change of the hydrogel could adjust the inter-nanosphere distance,dynamically controlling the formation or extinction of the SERS hottest spots on the same SERS substrate without influencing the spatial distribution of the analyte molecules.The timeshare SERS platform without the SERS hottest spots showed strong quantification capability,while when equipped with a substantial number of the SERS hottest spots exhibited ultrahigh sensitivity.We demonstrated quantitative and ultrasensitive detection of various analyte molecules using the quantitative and the sensitive mode of the timeshare SERS platform,respectively.We opened an avenue towards designing SERS substrates with both high sensitivity and strong quantification capability.
基金support from the Roy A.Wilkens Professorship Endowment。
文摘Interferometry is a crucial investigative technique used across diverse fields to achieve highprecision measurements.It works by analyzing the phase difference between two interfering waves,which results from variations in optical path lengths within an interferometer.We introduce a novel method for directly measuring changes in the phase difference within an optical interferometer,importantly,with the added advantage of a controllable enhancement factor.This approach is achieved through a two-step process:first,the optical phase difference is encoded into a sub-GHz radiofrequency(RF)signal using microwave-photonic manipulation;then,RF interferometry-assisted phase amplification is implemented at the destructive interference point.In our experiments,we demonstrate a phase sensitivity of 2.14 rad∕nm operating at 140 MHz using a miniature in-fiber Fabry-Pérot interferometer for sub-nanometer displacement sensing,which reveals a sensitivity magnification factor of 258.6.With further refinement,we anticipate that even higher enhancement factors can be achieved,paving the way for the development of cost-effective,ultrasensitive interferometry-based instruments for high-precision optical measurements.
基金supported by National Natural Science Foundation of China(Grant No.52272100)the Fund of Science and Technology on Advanced Ceramic Fibers and Composites Laboratory(Grant No.WDZC20215250507)the Fund of National Key Laboratory of Nuclear Reactor Technology of Nuclear Power Institute of China(KGSW-0324-0301-08)。
文摘The demand for sensors capable of operating in extreme environment of the fields,such as aerospace vehicles,aeroengines and fire protection,is rapidly increasing.However,developing flexible ceramic fibrous pressure sensors that combine high temperature stability with robust mechanical properties remains a significant challenge.Herein,through precise multi-scale process control,high-strength(2.1 MPa)TiC-SiC flexible fibrous membrane is successfully fabricated.The membrane exhibits exceptional thermal resistance(2000℃)and long–term thermal stability(1800℃ for 5 h)in the inert atmosphere.Meanwhile,the TiC-SiC fibrous membrane shows excellent oxidation resistance and still achieves strength of 1.8 MPa after being oxidized at 1200℃ for 1 h in air.Remarkably,TiC-SiC fibrous membrane withstands a load of approximately 1400 times its own weight and the ablation of butane flame(~1300℃)for at least 1 h without breaking.Notably,after heat treatment at 1800℃ for 5 h in an argon atmosphere,the TiC-SiC fibrous membrane even sustains pressure–sensing performance for up to 300 cycles.The membrane exhibits stable resistivity up to 900℃ and shows sensing stability under butane flame.The results of this work provide an effective and feasible solution to fill the research gap of flexible fibrous sensors for extreme environments.
基金financially supported by the National Natural Science Foundation of China(Grant No.32302764)Hunan Provincial Natural Science Foundation(Grant No.2024JJ5179)+1 种基金Key laboratory for the feed and biology technique of Xinjiang Uygur Autonomous Region(Grant No.XJSLSW-2023001)Hunan Herbivores Industry Technological System(Grant No.HARS-08)。
文摘Background Zearalenone(ZEN),a common mycotoxin in ruminant diets,could disturb the rumen ecosystem and impair rumen fermentation.Noticeably,ZEN has been shown to reduce the relative abundances of specific bacterial taxa that potentially possess quorum sensing(QS)functions,which are deemed essential for the microbial interactions and adaptations during rumen fermentation.Nonetheless,whether QS communications participate in the responses of rumen microbial fermentation to ZEN remains unknown.Therefore,the present trial was performed to explore the potential roles of QS during the alterations of rumen microbial fermentation by ZEN through a rumen simulation technique(RUSITEC)system,in a replicated 4×4 Latin square design.Results ZEN significantly(P<0.05)reduced QS signal autoinducer-2(AI-2),and tended to(P=0.051)downregulate QS signal C4-homoserine lactone(HSL).ZEN also significantly(P<0.05)decreased total volatile fatty acid(TVFA),acetate,propionate,isobutyrate,isovalerate,organic matter disappearance(OMD),neutral detergent fiber disappearance(NDFD),and acid detergent fiber disappearance(ADFD)in different manners.The linear discriminant analysis effect size(LEf Se)analysis indicated significantly(P<0.05)differential enrichments of a series of bacterial taxa such as Butyrivibrio_sp_X503,Rhizobium daejeonense,Hoylesella buccalis,Ezakiella coagulans,Enterococcus cecorum,Ruminococcus_sp_zg-924,Polystyrenella longa,and Methylacidimicrobium fagopyrum across different treatments.The phylogenetic investigation of communities by reconstruction of unobserved states 2(PICRUSt2)analysis suggested that QS were predicted to be significantly(P<0.05)affected by ZEN.The metabolomics analysis detected considerable significantly(P<0.05)differing metabolites and implied that ZEN challenge significantly(P<0.05)influenced the indole alkaloid biosynthesis,biosynthesis of alkaloids derived from shikimate pathway,and sesquiterpenoid and triterpenoid biosynthesis.Significant(P<0.05)interconnections of QS molecules with the differential rumen fermentation traits,differential bacterial taxa,and differential metabolites were exhibited by Spearman analysis.Conclusions ZEN negatively affected the QS signals of AI-2 and C4-HSL,which was found to correlate with the fluctuations in specific rumen fermentation characteristics,ruminal bacterial populations,and ruminal metabolisms.These interrelationships implied the potential involvement of QS in the reactions of rumen microbiota to ZEN contamination,and probably contributed to the inhibition of rumen fermentation.
基金supported by the Henan Province Key R&D Project under Grant 241111210400the Henan Provincial Science and Technology Research Project under Grants 252102211047,252102211062,252102211055 and 232102210069+2 种基金the Jiangsu Provincial Scheme Double Initiative Plan JSS-CBS20230474,the XJTLU RDF-21-02-008the Science and Technology Innovation Project of Zhengzhou University of Light Industry under Grant 23XNKJTD0205the Higher Education Teaching Reform Research and Practice Project of Henan Province under Grant 2024SJGLX0126。
文摘Accurate and efficient detection of building changes in remote sensing imagery is crucial for urban planning,disaster emergency response,and resource management.However,existing methods face challenges such as spectral similarity between buildings and backgrounds,sensor variations,and insufficient computational efficiency.To address these challenges,this paper proposes a novel Multi-scale Efficient Wavelet-based Change Detection Network(MewCDNet),which integrates the advantages of Convolutional Neural Networks and Transformers,balances computational costs,and achieves high-performance building change detection.The network employs EfficientNet-B4 as the backbone for hierarchical feature extraction,integrates multi-level feature maps through a multi-scale fusion strategy,and incorporates two key modules:Cross-temporal Difference Detection(CTDD)and Cross-scale Wavelet Refinement(CSWR).CTDD adopts a dual-branch architecture that combines pixel-wise differencing with semanticaware Euclidean distance weighting to enhance the distinction between true changes and background noise.CSWR integrates Haar-based Discrete Wavelet Transform with multi-head cross-attention mechanisms,enabling cross-scale feature fusion while significantly improving edge localization and suppressing spurious changes.Extensive experiments on four benchmark datasets demonstrate MewCDNet’s superiority over comparison methods:achieving F1 scores of 91.54%on LEVIR,93.70%on WHUCD,and 64.96%on S2Looking for building change detection.Furthermore,MewCDNet exhibits optimal performance on the multi-class⋅SYSU dataset(F1:82.71%),highlighting its exceptional generalization capability.
文摘Shallow landslides are strongly controlled by near-surface lithological variability,yet conventional geological maps are often too generalized to support accurate susceptibility assessment in complex terrains.This review synthesizes recent advances in remote sensing–based lithological mapping and evaluates their integration into landslide susceptibility modeling.Evidence from the literature indicates that remote sensing-derived lithological products,particularly those incorporating mineralogical information and higher spatial resolution,consistently outperform traditional geological maps in improving model accuracy and spatial detail,especially in heterogeneous environments.However,key challenges remain,including scale mismatches between surface observations and subsurface controls,limited ground validation,uncertainty propagation,and restricted model transferability across regions.The review identifies multi-sensor data fusion and explainable machine learning as the most promising directions for advancing lithological discrimination and model reliability.Future progress depends on integrating remote sensing with process-based understanding,improving validation strategies,and standardizing uncertainty reporting.These developments are essential for enabling more robust,scalable,and operationally relevant landslide susceptibility assessments in complex terrains.Lastly,we describe the directions of research that focus on multi-sensor fusion,explainable machine learning,UAV(Unmanned Aerial Vehicle)-enabled validation,and standardized uncertainty reporting that can help articulate landslide susceptibility assessment,making them even more robust and operationally significant.
基金Supported by Natural Science Foundation General Project of Heilongjiang Province(C2018050).
文摘As a vital food crop,rice is an important part of global food crops.Studying the spatiotemporal changes in rice cultivation facilitates early prediction of production risks and provides support for agricultural policy decisions related to rice.With the increasing application of satellite remote sensing technology in crop monitoring,remote sensing for rice cultivation has emerged as a novel approach,offering new perspectives for monitoring rice planting.This paper briefly outlined the current research and development status of satellite remote sensing for monitoring rice cultivation both at home and abroad.Foreign scholars have made innovations in data sources and methodologies for satellite remote sensing monitoring,and utilized multi-source satellite information and machine learning algorithms to enhance the accuracy of rice planting monitoring.Scholars in China have achieved significant results in the study of satellite remote sensing for monitoring rice cultivation.Their research and application in monitoring rice planting areas provide valuable references for agricultural production management.However,satellite remote sensing monitoring of rice still faces challenges such as low spatiotemporal resolution and difficulties related to cloud cover and data fusion,which require further in-depth investigation.Additionally,there are shortcomings in the accuracy of remote sensing monitoring for fragmented farmland plots and smallholder farming.To address these issues,future efforts should focus on developing multi-source heterogeneous data fusion analysis technologies and researching monitoring systems.These advancements are expected to enable high-precision large-scale acquisition of rice planting information,laying a foundation for future smart agriculture.
