In an academic environment increasingly shaped by metrics and the imperatives of“publish or perish”,it is rare to encounter a leading scientist willing to interweave personal narrative with conceptual reflection.The...In an academic environment increasingly shaped by metrics and the imperatives of“publish or perish”,it is rare to encounter a leading scientist willing to interweave personal narrative with conceptual reflection.The Soul of Geography by Fu(2025)achieves precisely this.The book resists simple categorisation:it is neither a conventional monograph nor a memoir,but rather a hybrid text that integrates autobiography,disciplinary reflection,and scientific arguments.In doing so,Fu articulates not only the trajectory of his own career but also a vision of geography as a discipline of theoretical depth and practical relevance.展开更多
This paper expands Prasenjit Duara’s proposal that Asian religions and philosophies offer hope for a sustainable future.After outlining Duara’s sociology of history that describes the crisis of global modernity in t...This paper expands Prasenjit Duara’s proposal that Asian religions and philosophies offer hope for a sustainable future.After outlining Duara’s sociology of history that describes the crisis of global modernity in terms of three global changes,namely the rise of non-western nations,the crisis of climate change,and the decline of religious or transcendent sources of authority,Duara proposes that grassroots organizations coupled with Asian religious and philosophical beliefs and practices offer different ways of understanding the relationship between the person and the environment,and between our universal-planetary interests and our national interests.Drawing from Asian and Pacific indigenous teachings,I propose a type of depth ecology called“existential parity”that all things and creatures have value,generating a moral corollary called the“existential commitment”that humans take responsibility for the environment and each other.The existential commitment offers an environmental ethics that promotes sustainable agriculture to feed the world’s population.Pacific agroforestry practices can be implemented in urban settings to help mitigate climate change and food shortages.展开更多
The initial noise present in the depth images obtained with RGB-D sensors is a combination of hardware limitations in addition to the environmental factors,due to the limited capabilities of sensors,which also produce...The initial noise present in the depth images obtained with RGB-D sensors is a combination of hardware limitations in addition to the environmental factors,due to the limited capabilities of sensors,which also produce poor computer vision results.The common image denoising techniques tend to remove significant image details and also remove noise,provided they are based on space and frequency filtering.The updated framework presented in this paper is a novel denoising model that makes use of Boruta-driven feature selection using a Long Short-Term Memory Autoencoder(LSTMAE).The Boruta algorithm identifies the most useful depth features that are used to maximize the spatial structure integrity and reduce redundancy.An LSTMAE is then used to process these selected features and model depth pixel sequences to generate robust,noise-resistant representations.The system uses the encoder to encode the input data into a latent space that has been compressed before it is decoded to retrieve the clean image.Experiments on a benchmark data set show that the suggested technique attains a PSNR of 45 dB and an SSIM of 0.90,which is 10 dB higher than the performance of conventional convolutional autoencoders and 15 times higher than that of the wavelet-based models.Moreover,the feature selection step will decrease the input dimensionality by 40%,resulting in a 37.5%reduction in training time and a real-time inference rate of 200 FPS.Boruta-LSTMAE framework,therefore,offers a highly efficient and scalable system for depth image denoising,with a high potential to be applied to close-range 3D systems,such as robotic manipulation and gesture-based interfaces.展开更多
This study aims to develop an accurate and robust machine learning model to predict the carbonation depth of fly ash concrete,overcoming the limitations of traditional predictive methods.Five ensemble-based models,suc...This study aims to develop an accurate and robust machine learning model to predict the carbonation depth of fly ash concrete,overcoming the limitations of traditional predictive methods.Five ensemble-based models,such as adaptive boosting(AdaBoost),categorical boosting(CatBoost),gradient boosting regressor(GBR),hist gradient boosting regressor(HistGBR),and extreme gradient boosting(XGBoost),were developed and optimized using 729 high-quality dataset points incorporating seven input parameters,including cement,CO_(2),exposure time,water-binder ratio,fly ash,curing time,and compressive strength.Several performance evaluation metrics were used to compare the models.The GBR model emerged as the best-performing model,based on high coefficient of determination(R^(2))values and balanced error metrics across both validation and testing datasets.While all models performed exceptionally well on the training data,GBR demonstrated superior generalization capability,with R^(2) values of 0.9438 on the validation set and 0.9310 on the testing set.Furthermore,its low mean squared error(MSE),root mean square error(RMSE),mean absolute error(MAE),and median absolute error(MdAE)confirmed its robustness and accuracy.Moreover,shapley additive explanations(SHAP)analysis enhanced the interpretability of predictions,highlighting the curing time and exposure time as the most critical drivers of carbonation depth.展开更多
Objective:To explore the relationship between anesthetic depth and surgical stress response in minimally invasive cardiothoracic surgery.Methods:A total of 89 patients who underwent thoracoscopic minimally invasive ca...Objective:To explore the relationship between anesthetic depth and surgical stress response in minimally invasive cardiothoracic surgery.Methods:A total of 89 patients who underwent thoracoscopic minimally invasive cardiothoracic surgery in our hospital from June 2024 to December 2024 were selected as the research objects.They were divided into the light anesthesia group(n=45)and the deep anesthesia group(n=44).The vital signs at different intraoperative nodes and perioperative stress status of the two groups were compared.Results:Before lesion resection and after surgery,the mean arterial pressure and heart rate of the deep anesthesia group were lower than those of the light anesthesia group,with statistically significant differences.Conclusion:In thoracoscopic minimally invasive cardiothoracic surgery,deep anesthesia can effectively control the patient’s surgical stress response,but the postoperative awakening time is longer;patients under light anesthesia have a shorter awakening time,but the intraoperative stress response is obvious.展开更多
Presented in this study is a novel method for estimating the depth of single underwater source in shallow water,utilizing vector sensors.The approach leverages the depth distribution of the broadband Stokes parameters...Presented in this study is a novel method for estimating the depth of single underwater source in shallow water,utilizing vector sensors.The approach leverages the depth distribution of the broadband Stokes parameters to estimate source depth accurately.Unlike traditional matched field processing(MFP)and matched mode processing(MMP),the proposed approach can estimate source depth directly from the data received by sensors without requiring complete environmental information.Firstly,the broadband Stokes parameters(BSP)are established using the normal mode theory.Then the nonstationary phase approximation is used to simplify the theoretical derivation,which is necessary when dealing with broadband integrals.Additionally,range terms of the BSP are eliminated by normalization.By analyzing the depth distribution of the normalized broadband Stokes parameters(NBSP),it is found that the NBSP exhibit extreme values at the source depth,which can be used for source depth estimation.So the proposed depth estimation method is based on searching the peaks of the NBSP.Simulations show that this method is effective in relatively simple shallow water environments.Finally,the effect of source range,frequency bandwidth,sound speed profile(SSP),water depth,and signal-to-noise ratio(SNR)are studied.The findings indicate that the proposed method can accurately estimate the source depth when the SNR is greater than-5 d B and does not need to consider model mismatch issues.Additionally,variations in environmental parameters have minimal impact on estimation accuracy.Compared to MFP,the proposed method requires a higher SNR,but demonstrates superior robustness against fluctuations in environmental parameters.展开更多
A CFD-based numerical model was employed to quantitatively analyze the flow characteristics of double-side-blown gas−liquid flow.Key parameters were extracted,and Spearman correlation analysis was used to quantify the...A CFD-based numerical model was employed to quantitatively analyze the flow characteristics of double-side-blown gas−liquid flow.Key parameters were extracted,and Spearman correlation analysis was used to quantify the relationships among bubble behavior,circulating flow,and liquid oscillations.The results show that periodic bubble behavior under steady injection drives the circulating flow of the liquid on both sides.The asynchronism of bubble behavior on both sides results in the alternation of circulating intensity,which significantly enhances gas−liquid mixing efficiency at certain liquid levels of 200 and 220 mm.Flow patterns of the double-side-blown process are classified into weak circulation,strong−weak alternating circulation,and strong circulation modes based on the influence of circulating flows on the penetration depth.The penetration depth in the strong−weak alternating circulation mode is generally greater than that in the single-side-blown process.The imbalance of circulating intensities on both sides primarily leads to the stable fluctuation in the injecting direction,which reveals the appearance of periodic oscillations in the molten bath.The effect of control parameters such as liquid level and gas flow rate on the liquid oscillations were discussed.展开更多
While the Ordos Basin is recognized for its substantial hydrocarbon exploration prospects,its rugged loess tableland terrain has rendered seismic exploration exceptionally challenging[1-3].Persistent obstacles such as...While the Ordos Basin is recognized for its substantial hydrocarbon exploration prospects,its rugged loess tableland terrain has rendered seismic exploration exceptionally challenging[1-3].Persistent obstacles such as complex 3D survey planning,low signal-tonoise ratio raw data,inadequate near-surface velocity modeling,and imaging inaccuracy have long hindered the advancement of seismic exploration across this region.Through a problem-solving approach rooted in geological target analysis,this research systematically investigates the behavioral patterns of nodal seismometer-based high-density seismic acquisition in loess plateau.Tailored advancements in waveform enhancement and depth velocity modelling methodologies have been engineered.Field validations confirm that the optimized workflow demonstrates marked improvements in amplitude preservation and imaging resolution,offering novel insights for future reservoir characterization endeavors.展开更多
Accurately estimating depth from underwater monocular images is essential for the target tracking task of unmanned underwater vehicles.This work proposes a method based on the Lpg-Lap Unet architecture.First,the Unet ...Accurately estimating depth from underwater monocular images is essential for the target tracking task of unmanned underwater vehicles.This work proposes a method based on the Lpg-Lap Unet architecture.First,the Unet architecture integrates Laplacian pyramid depth residuals and Sobel operators to improve the boundary details in depth images,which may suffer from the feature loss caused by upsampling and the blurriness of underwater images.Multiscale local planar guidance layers then fully exploit the intermediate depth features,and a comprehensive loss function ensures robustness and accuracy.Experimental results on benchmarks demonstrate the effectiveness of Lpg-Lap Unet and its superior performance over state-of-the-art models.An underwater target tracking system is then designed to further validate its real-time capabilities in the AirSim simulation platform.展开更多
Bathymetric measurement of shallow water is of fundamental importance to coastal environment research and resource management.However,there are still great challenges in estimating water depth using satellite observat...Bathymetric measurement of shallow water is of fundamental importance to coastal environment research and resource management.However,there are still great challenges in estimating water depth using satellite observations in turbid coastal waters.In this paper,we developed a physicsenhanced deep neural network to estimate bathymetry of highly turbid waters of the Changjiang(Yangtze)River estuary from dual-polarized synthetic aperture radar(SAR)images.Sentinel-1A/B SAR images with a spatial resolution of 20 m×22 m were collected and matched with water depth data from nautical charts during 2017-2023.For the input parameters of the model,in addition to the normalized radar backscatter cross section(NRCS)at single polarization and incidence angle,the impacts of both polarimetric characteristics and physical environmental factors on model performance were discussed in detail.Results of feature importance analysis and sensitivity experiments indicate that the polarization ratio and NRCS after removing the influence of background sea surface wind field make significant contributions to the bathymetry retrieval model.The root mean square error(RMSE)of SAR derived water depth decreases from 1.44 to 0.78 m within 0-30-m depth,and the mean relative error(MRE)is reduced from 15.6%to 8.6%.Compared with other machine learning models such as ResNet,XGBoost,and Random Forest,the MRE is reduced by 3.9%,5.7%,and 7.4%,respectively.The spatial distribution of SAR derived water depth also exhibits a high degree of consistency with observations,demonstrating the great potential of the model in estimating the depth of turbid shallow waters.展开更多
Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in th...Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many areas.In this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,China.The two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction results.In addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.展开更多
Rare earth-doped inorganic compounds contribute mostly to the family of persistent luminescent materials due to the versatile energy levels of rare earth ions.One of the key research aims is to match the trap level st...Rare earth-doped inorganic compounds contribute mostly to the family of persistent luminescent materials due to the versatile energy levels of rare earth ions.One of the key research aims is to match the trap level stemming from the doped rare earth ion or intrinsic defects to the electronic structure of the host,and therefore thermoluminescence measurement becomes a radical technology in studying trap depth,which is one of the significant parameters that determine the properties of persistent luminescence and photostimulated luminescence.However,the results of trap depth obtained by different thermoluminescence methods are quite different so that they are not comparable.Herein,we analyzed different thermoluminescence methods,selected and improved the traditional peak position method of T_(m)/500 to be E=(-0.94Inβ+30.09)kT_(m).Only the experimental heating rate(β)is needed additionally,but the accuracy is improved greatly in most cases.This convenient and accurate method will accelerate the discovery of novel rare earth-doped materials.展开更多
Spatial computing and augmented reality are advancing rapidly,with the goal of seamlessly blending virtual and physical worlds.However,traditional depth-sensing systems are bulky and energy-intensive,limiting their us...Spatial computing and augmented reality are advancing rapidly,with the goal of seamlessly blending virtual and physical worlds.However,traditional depth-sensing systems are bulky and energy-intensive,limiting their use in wearable devices.To overcome this,recent research by X.Liu et al.presents a compact binocular metalens-based depth perception system that integrates efficient edge detection through an advanced neural network.This system enables accurate,realtime depth mapping even in complex environments,enhancing potential applications in augmented reality,robotics,and autonomous systems.展开更多
The accurate identification of microporosity is crucial for the characterization of hydrocarbon reservoir permeability and production.Scanning electron microscopy(SEM)is among the limited number of methods available t...The accurate identification of microporosity is crucial for the characterization of hydrocarbon reservoir permeability and production.Scanning electron microscopy(SEM)is among the limited number of methods available to directly observe the microscopic structure of the hydrocarbon reservoir rocks.Nevertheless,precise segmentation of microscopic pores at different depths in SEM images remains an unsolved challenge,known as the‘depth-related resolution loss'problem.Therefore,in this study,a 3D reconstruction technique for regions of interest(ROI)was developed for in-depth pixel analysis and differentiation among various depths of SEM images.The processed SEM images,together with the processing outcomes of this technique,were used as the input database to train a stochastic depth with multi-channel residual pathways(SdstMcrp)deep learning model programmed in Python to develop a tool for segmenting the microscopic pore spaces in SEM images obtained from the Beibuwan Basin.The more accurate segmentation helped to detect an average of 1.2 times more microporosity in SEM images,accounting for about 1.6 times more pixels and 1.2 times more pore surface area.Finally,the impact of the accurate segmentation on the calculation of permeability,a significant reservoir production property,was investigated using fractal geometry models and sensitivity analysis.The results showed that the obtained permeability values would vary by a factor of 6,which represents a considerable difference.These findings demonstrate that the proposed models can effectively identify features across a wide range of grayscale values in SEM images.展开更多
A 3D crustal model was constructed using a combination of cutting-edge techniques,which were integrated to provide a density model for Egypt and address the sporadic distribution of seismic data.These techniques inclu...A 3D crustal model was constructed using a combination of cutting-edge techniques,which were integrated to provide a density model for Egypt and address the sporadic distribution of seismic data.These techniques include obtaining gravity data from the Gravity Field and Steady-State Ocean Circulation Explorer(GOCE),creating seismic profiles,analyzing the receiver functions of seismic data,obtaining information from boreholes,and providing geological interpretations.GOCE satellite gravity data were processed to construct a preliminary model based on nonlinear inversions of the data.A regional crustal thickness model was developed using receiver functions,seismic refraction profiles,and geological insights.The inverted model was validated using borehole data and compared with seismic estimates.The model exhibited strong consistency and revealed a correlation between crustal thickness,geology,and tectonics of Egypt.It showed that the shallowest depths of the Moho are located in the north along the Mediterranean Sea and in the eastern part along the Red Sea,reflecting an oceanic plate with a thin,high-density crust.The deepest Moho depths are located in the southwestern part of Egypt,Red Sea coastal mountains,and Sinai Peninsula.The obtained 3D model of crustal thickness provided finely detailed Moho depth estimates that aligned closely with geology and tectonic characteristics of Egypt,contributing valuable insights into the subsurface structure and tectonic processes of region.展开更多
The active sound absorption technique excels in mitigating low-frequency sound waves,yet it falls short when dealing with medium and high-frequency sound waves.To enhance the sound-absorbing effect of medium and high-...The active sound absorption technique excels in mitigating low-frequency sound waves,yet it falls short when dealing with medium and high-frequency sound waves.To enhance the sound-absorbing effect of medium and high-frequency sound waves,a novel semi-active sound absorption method has been introduced.This method modulates the surface impedance of a loudspeaker positioned behind the sound-absorbing material,thereby altering the sound absorption coefficient.The theoretical sound absorption coefficient is calculated using MATLAB and compared with the experimental one.Results show that the method can effectively modulates the absorption coefficient in response to varying incident sound wave frequencies,ensuring that it remains at its peak value.展开更多
To address the challenges posed by tunnel construction in the alpine region,silica fume mixed concrete is commonly used as a construction material.The correlation between silica fume content and the lining life requir...To address the challenges posed by tunnel construction in the alpine region,silica fume mixed concrete is commonly used as a construction material.The correlation between silica fume content and the lining life requires immediate investigation.In view of this phenomenon,the durability of unit lining concrete is predicted by analyzing three key indicators:carbonation depth,relative dynamic elastic modulus,and residual quality.This prediction is achieved by integrating the Entropy Weight Method,Grey theory life prediction model and BP artificial neural networks using data from tests and predictions of these indicators.Then,the Entropy Weight-Grey theory-BP Network Model is compared with other methods to analyze the predicted life.Finally,verify the sci-entificity of this model,and the optimum silica fume content of unit concrete lining is verified.The results showed,1)The addition of silica fume will accelerate the carbonization of unit concrete lining,and slow down the freeze-thaw cycle and sulfate erosion.2)The utilization of artificial neural networks is essential for enhancing the realism of the data,as it emphasizes the significance of silica fume content.3)Silica fume content of 10%results in the longest life and is the most suitable for lining construction.4)A comparison between single-factor and multi-factor predictions indicates that the multi-factor approach yields a longer maximum life.This improvement can be attributed to the inclusion of additional factors,such as freeze-thaw cycles and carbonation,which enhance the predicted life when employing these methods.In conclusion,the Entropy Weight-Grey Theory-BP Network life prediction Model is well-suited for tunnel lining in the alpine sulfate area of northwest China.展开更多
Rectal neuroendocrine tumor(rNET)is an indolent malignancy often detected during colonoscopy screening.The incidence of rNET has increased approximately 10-fold over the past 30 years.Most rNETs detected during screen...Rectal neuroendocrine tumor(rNET)is an indolent malignancy often detected during colonoscopy screening.The incidence of rNET has increased approximately 10-fold over the past 30 years.Most rNETs detected during screening endoscopy are small,measuring<10 mm.Current guidelines recommend endoscopic resection for small,well-differentiated rNET using modified endoscopic submucosal resection(mEMR)or endoscopic submucosal dissection.However,the optimal endoscopic treatment method remains uncertain.This paper summarizes the evidence on mEMR with submucosal stretching,mEMR without submucosal stretching,endoscopic submucosal dissection and endoscopic full-thickness resection.Given that rNETs often exhibit submucosal invasion,achieving adequate resection depth is crucial to ensure histological complete resection.mEMR with submucosal stretching appears favorable due to its high rate of histological complete resection,safety and convenience.Risk factors associated with lymph node and distant metastases are also discussed.A treatment algorithm is proposed to facilitate clinical decision-making.展开更多
A new type of 785 nm semiconductor laser device has been proposed.The thin cladding and mode expansion layer structure incorporated into the epitaxy on the p-side significantly impacts the regulation of grating etchin...A new type of 785 nm semiconductor laser device has been proposed.The thin cladding and mode expansion layer structure incorporated into the epitaxy on the p-side significantly impacts the regulation of grating etching depth.Thinning of the p-side waveguide layer makes the light field bias to the n-side cladding layer.By coordinating the confinement effect of the cladding layer,the light confinement factor on the p-side is regulated.On the other hand,the introduction of a mode expansion layer facilitates the expansion of the mode profile on the p side cladding layer.Both these factors contribute positively to reducing the grating etching depth.Compared to the reported epitaxial structures of symmetric waveguides,the new structure significantly reduces the etching depth of the grating while ensuring adequate reflection intensity and maintaining resonance.Moreover,to improve the output performance of the device,the new epitaxial structure has been optimized.Based on the traditional epitaxial structure,an energy release layer and an electron blocking layer are added to improve the electronic recombination efficiency.This improved structure has an output performance comparable to that of a symmetric waveguide,despite being able to have a smaller gain area.展开更多
Based on Moho and Curie depth,heat flow,and upper mantle S-wave velocity anomaly,we infer the thermo-chemical structure of the lithospheres in Africa and surrounding oceans.The Moho depth is derived from gravity anoma...Based on Moho and Curie depth,heat flow,and upper mantle S-wave velocity anomaly,we infer the thermo-chemical structure of the lithospheres in Africa and surrounding oceans.The Moho depth is derived from gravity anomaly using the Parker-Oldenburg method,with constraints from seismic Moho.Crustal stratification defined by Curie-Moho depth difference shows that thermal and strong compositional processes may have shaped the lithospheric architecture of the African continental plate.Moho and Curie depths indicate the southern and eastern African cratons have thermochemical structures different from the West African Craton.Large Curie-Moho depth difference in southern and eastern Africa aligns with the low velocity anomaly originated from the core-mantle boundary.Mantle upwelling from the African low-velocity anomaly presumably induced partial melting at great depth,and the release of mineral-rich fluid and large amounts of volatile components facilitates a regional metasomatism,and results in a depleted,predominantly felsic,low-density paramagnetic crust.Mantle xenolith in kimberlites and volcanic rocks supports metasomatism by melts transmitted through narrow conduits as an intermittent or continuous upward flux of mineral-rich fluid.Alignment of the Curie-Moho depth difference at the intra-plate volcanic province correlates with weak lithospheric strength along the corridor connecting the intra-plate volcanic province with the Ethiopian plateau,suggesting a pathway for thermochemical asthenospheric flow.Crustal stratification and compositional-driven density layering support crustal buoyancy and uplift in the Hoggar,and southern and eastern Africa.A magnetized uppermost mantle is prevalent in the entire oceanic region,except at large igneous provinces(LIPs),volcanic seamounts,and oceanic plateaus,which have partial paramagnetic crusts.Our results support thermochemical upwelling related to the low velocity anomaly beneath the African plate.展开更多
文摘In an academic environment increasingly shaped by metrics and the imperatives of“publish or perish”,it is rare to encounter a leading scientist willing to interweave personal narrative with conceptual reflection.The Soul of Geography by Fu(2025)achieves precisely this.The book resists simple categorisation:it is neither a conventional monograph nor a memoir,but rather a hybrid text that integrates autobiography,disciplinary reflection,and scientific arguments.In doing so,Fu articulates not only the trajectory of his own career but also a vision of geography as a discipline of theoretical depth and practical relevance.
文摘This paper expands Prasenjit Duara’s proposal that Asian religions and philosophies offer hope for a sustainable future.After outlining Duara’s sociology of history that describes the crisis of global modernity in terms of three global changes,namely the rise of non-western nations,the crisis of climate change,and the decline of religious or transcendent sources of authority,Duara proposes that grassroots organizations coupled with Asian religious and philosophical beliefs and practices offer different ways of understanding the relationship between the person and the environment,and between our universal-planetary interests and our national interests.Drawing from Asian and Pacific indigenous teachings,I propose a type of depth ecology called“existential parity”that all things and creatures have value,generating a moral corollary called the“existential commitment”that humans take responsibility for the environment and each other.The existential commitment offers an environmental ethics that promotes sustainable agriculture to feed the world’s population.Pacific agroforestry practices can be implemented in urban settings to help mitigate climate change and food shortages.
文摘The initial noise present in the depth images obtained with RGB-D sensors is a combination of hardware limitations in addition to the environmental factors,due to the limited capabilities of sensors,which also produce poor computer vision results.The common image denoising techniques tend to remove significant image details and also remove noise,provided they are based on space and frequency filtering.The updated framework presented in this paper is a novel denoising model that makes use of Boruta-driven feature selection using a Long Short-Term Memory Autoencoder(LSTMAE).The Boruta algorithm identifies the most useful depth features that are used to maximize the spatial structure integrity and reduce redundancy.An LSTMAE is then used to process these selected features and model depth pixel sequences to generate robust,noise-resistant representations.The system uses the encoder to encode the input data into a latent space that has been compressed before it is decoded to retrieve the clean image.Experiments on a benchmark data set show that the suggested technique attains a PSNR of 45 dB and an SSIM of 0.90,which is 10 dB higher than the performance of conventional convolutional autoencoders and 15 times higher than that of the wavelet-based models.Moreover,the feature selection step will decrease the input dimensionality by 40%,resulting in a 37.5%reduction in training time and a real-time inference rate of 200 FPS.Boruta-LSTMAE framework,therefore,offers a highly efficient and scalable system for depth image denoising,with a high potential to be applied to close-range 3D systems,such as robotic manipulation and gesture-based interfaces.
文摘This study aims to develop an accurate and robust machine learning model to predict the carbonation depth of fly ash concrete,overcoming the limitations of traditional predictive methods.Five ensemble-based models,such as adaptive boosting(AdaBoost),categorical boosting(CatBoost),gradient boosting regressor(GBR),hist gradient boosting regressor(HistGBR),and extreme gradient boosting(XGBoost),were developed and optimized using 729 high-quality dataset points incorporating seven input parameters,including cement,CO_(2),exposure time,water-binder ratio,fly ash,curing time,and compressive strength.Several performance evaluation metrics were used to compare the models.The GBR model emerged as the best-performing model,based on high coefficient of determination(R^(2))values and balanced error metrics across both validation and testing datasets.While all models performed exceptionally well on the training data,GBR demonstrated superior generalization capability,with R^(2) values of 0.9438 on the validation set and 0.9310 on the testing set.Furthermore,its low mean squared error(MSE),root mean square error(RMSE),mean absolute error(MAE),and median absolute error(MdAE)confirmed its robustness and accuracy.Moreover,shapley additive explanations(SHAP)analysis enhanced the interpretability of predictions,highlighting the curing time and exposure time as the most critical drivers of carbonation depth.
文摘Objective:To explore the relationship between anesthetic depth and surgical stress response in minimally invasive cardiothoracic surgery.Methods:A total of 89 patients who underwent thoracoscopic minimally invasive cardiothoracic surgery in our hospital from June 2024 to December 2024 were selected as the research objects.They were divided into the light anesthesia group(n=45)and the deep anesthesia group(n=44).The vital signs at different intraoperative nodes and perioperative stress status of the two groups were compared.Results:Before lesion resection and after surgery,the mean arterial pressure and heart rate of the deep anesthesia group were lower than those of the light anesthesia group,with statistically significant differences.Conclusion:In thoracoscopic minimally invasive cardiothoracic surgery,deep anesthesia can effectively control the patient’s surgical stress response,but the postoperative awakening time is longer;patients under light anesthesia have a shorter awakening time,but the intraoperative stress response is obvious.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12274348 and 12004335)the National Key Research and Development Program of China(Grant No.2024YFC2813800)。
文摘Presented in this study is a novel method for estimating the depth of single underwater source in shallow water,utilizing vector sensors.The approach leverages the depth distribution of the broadband Stokes parameters to estimate source depth accurately.Unlike traditional matched field processing(MFP)and matched mode processing(MMP),the proposed approach can estimate source depth directly from the data received by sensors without requiring complete environmental information.Firstly,the broadband Stokes parameters(BSP)are established using the normal mode theory.Then the nonstationary phase approximation is used to simplify the theoretical derivation,which is necessary when dealing with broadband integrals.Additionally,range terms of the BSP are eliminated by normalization.By analyzing the depth distribution of the normalized broadband Stokes parameters(NBSP),it is found that the NBSP exhibit extreme values at the source depth,which can be used for source depth estimation.So the proposed depth estimation method is based on searching the peaks of the NBSP.Simulations show that this method is effective in relatively simple shallow water environments.Finally,the effect of source range,frequency bandwidth,sound speed profile(SSP),water depth,and signal-to-noise ratio(SNR)are studied.The findings indicate that the proposed method can accurately estimate the source depth when the SNR is greater than-5 d B and does not need to consider model mismatch issues.Additionally,variations in environmental parameters have minimal impact on estimation accuracy.Compared to MFP,the proposed method requires a higher SNR,but demonstrates superior robustness against fluctuations in environmental parameters.
基金financial support for this research work from the National Key Research and Development Program of China(No.2022YFB3304901)。
文摘A CFD-based numerical model was employed to quantitatively analyze the flow characteristics of double-side-blown gas−liquid flow.Key parameters were extracted,and Spearman correlation analysis was used to quantify the relationships among bubble behavior,circulating flow,and liquid oscillations.The results show that periodic bubble behavior under steady injection drives the circulating flow of the liquid on both sides.The asynchronism of bubble behavior on both sides results in the alternation of circulating intensity,which significantly enhances gas−liquid mixing efficiency at certain liquid levels of 200 and 220 mm.Flow patterns of the double-side-blown process are classified into weak circulation,strong−weak alternating circulation,and strong circulation modes based on the influence of circulating flows on the penetration depth.The penetration depth in the strong−weak alternating circulation mode is generally greater than that in the single-side-blown process.The imbalance of circulating intensities on both sides primarily leads to the stable fluctuation in the injecting direction,which reveals the appearance of periodic oscillations in the molten bath.The effect of control parameters such as liquid level and gas flow rate on the liquid oscillations were discussed.
文摘While the Ordos Basin is recognized for its substantial hydrocarbon exploration prospects,its rugged loess tableland terrain has rendered seismic exploration exceptionally challenging[1-3].Persistent obstacles such as complex 3D survey planning,low signal-tonoise ratio raw data,inadequate near-surface velocity modeling,and imaging inaccuracy have long hindered the advancement of seismic exploration across this region.Through a problem-solving approach rooted in geological target analysis,this research systematically investigates the behavioral patterns of nodal seismometer-based high-density seismic acquisition in loess plateau.Tailored advancements in waveform enhancement and depth velocity modelling methodologies have been engineered.Field validations confirm that the optimized workflow demonstrates marked improvements in amplitude preservation and imaging resolution,offering novel insights for future reservoir characterization endeavors.
基金partially supported by the Natural Science Foundation of Shandong Province,China(No.ZR2023ME009)the National Natural Science Foundation of China(No.51909252)。
文摘Accurately estimating depth from underwater monocular images is essential for the target tracking task of unmanned underwater vehicles.This work proposes a method based on the Lpg-Lap Unet architecture.First,the Unet architecture integrates Laplacian pyramid depth residuals and Sobel operators to improve the boundary details in depth images,which may suffer from the feature loss caused by upsampling and the blurriness of underwater images.Multiscale local planar guidance layers then fully exploit the intermediate depth features,and a comprehensive loss function ensures robustness and accuracy.Experimental results on benchmarks demonstrate the effectiveness of Lpg-Lap Unet and its superior performance over state-of-the-art models.An underwater target tracking system is then designed to further validate its real-time capabilities in the AirSim simulation platform.
基金Supported by the National Natural Science Foundation of China(Nos.T2261149752,41976163,42476172)。
文摘Bathymetric measurement of shallow water is of fundamental importance to coastal environment research and resource management.However,there are still great challenges in estimating water depth using satellite observations in turbid coastal waters.In this paper,we developed a physicsenhanced deep neural network to estimate bathymetry of highly turbid waters of the Changjiang(Yangtze)River estuary from dual-polarized synthetic aperture radar(SAR)images.Sentinel-1A/B SAR images with a spatial resolution of 20 m×22 m were collected and matched with water depth data from nautical charts during 2017-2023.For the input parameters of the model,in addition to the normalized radar backscatter cross section(NRCS)at single polarization and incidence angle,the impacts of both polarimetric characteristics and physical environmental factors on model performance were discussed in detail.Results of feature importance analysis and sensitivity experiments indicate that the polarization ratio and NRCS after removing the influence of background sea surface wind field make significant contributions to the bathymetry retrieval model.The root mean square error(RMSE)of SAR derived water depth decreases from 1.44 to 0.78 m within 0-30-m depth,and the mean relative error(MRE)is reduced from 15.6%to 8.6%.Compared with other machine learning models such as ResNet,XGBoost,and Random Forest,the MRE is reduced by 3.9%,5.7%,and 7.4%,respectively.The spatial distribution of SAR derived water depth also exhibits a high degree of consistency with observations,demonstrating the great potential of the model in estimating the depth of turbid shallow waters.
基金supported by the National Natural Science Foundation of China [grant numbers 42088101 and 42375048]。
文摘Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many areas.In this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,China.The two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction results.In addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.
基金Project supported by the National Natural Science Foundation of China(52372134,12274023)the Fundamental Re search Funds for the Central Universities(FRF-EYIT-23-04)。
文摘Rare earth-doped inorganic compounds contribute mostly to the family of persistent luminescent materials due to the versatile energy levels of rare earth ions.One of the key research aims is to match the trap level stemming from the doped rare earth ion or intrinsic defects to the electronic structure of the host,and therefore thermoluminescence measurement becomes a radical technology in studying trap depth,which is one of the significant parameters that determine the properties of persistent luminescence and photostimulated luminescence.However,the results of trap depth obtained by different thermoluminescence methods are quite different so that they are not comparable.Herein,we analyzed different thermoluminescence methods,selected and improved the traditional peak position method of T_(m)/500 to be E=(-0.94Inβ+30.09)kT_(m).Only the experimental heating rate(β)is needed additionally,but the accuracy is improved greatly in most cases.This convenient and accurate method will accelerate the discovery of novel rare earth-doped materials.
基金financially supported by the POSCO-POSTECH-RIST Convergence Research Center program funded by POSCOthe National Research Foundation (NRF) grants (RS-2024-00462912, RS-2024-00416272, RS-2024-00337012, RS-2024-00408446) funded by the Ministry of Science and ICT (MSIT) of the Korean government+2 种基金the Korea Evaluation Institute of Industrial Technology (KEIT) grant (No. 1415185027/20019169, Alchemist project) funded by the Ministry of Trade, Industry and Energy (MOTIE) of the Korean governmentthe Soseon Science fellowship funded by Community Chest of Koreathe NRF PhD fellowship (RS-2023-00275565) funded by the Ministry of Education (MOE) of the Korean government。
文摘Spatial computing and augmented reality are advancing rapidly,with the goal of seamlessly blending virtual and physical worlds.However,traditional depth-sensing systems are bulky and energy-intensive,limiting their use in wearable devices.To overcome this,recent research by X.Liu et al.presents a compact binocular metalens-based depth perception system that integrates efficient edge detection through an advanced neural network.This system enables accurate,realtime depth mapping even in complex environments,enhancing potential applications in augmented reality,robotics,and autonomous systems.
基金the Natural Science Foundation of Shandong Province of China(Nos.ZR2022QD080 , ZR2025MS575)the National Natural Science Foundation of China(Nos.W25322063,42250410333,52250410357)+1 种基金the Fundamental Research Funds for the Central Universities,CHD(No.300102263103)the Young Talent Fund of Association for Science and Technology in Shaanxi,China(No.20230703)。
文摘The accurate identification of microporosity is crucial for the characterization of hydrocarbon reservoir permeability and production.Scanning electron microscopy(SEM)is among the limited number of methods available to directly observe the microscopic structure of the hydrocarbon reservoir rocks.Nevertheless,precise segmentation of microscopic pores at different depths in SEM images remains an unsolved challenge,known as the‘depth-related resolution loss'problem.Therefore,in this study,a 3D reconstruction technique for regions of interest(ROI)was developed for in-depth pixel analysis and differentiation among various depths of SEM images.The processed SEM images,together with the processing outcomes of this technique,were used as the input database to train a stochastic depth with multi-channel residual pathways(SdstMcrp)deep learning model programmed in Python to develop a tool for segmenting the microscopic pore spaces in SEM images obtained from the Beibuwan Basin.The more accurate segmentation helped to detect an average of 1.2 times more microporosity in SEM images,accounting for about 1.6 times more pixels and 1.2 times more pore surface area.Finally,the impact of the accurate segmentation on the calculation of permeability,a significant reservoir production property,was investigated using fractal geometry models and sensitivity analysis.The results showed that the obtained permeability values would vary by a factor of 6,which represents a considerable difference.These findings demonstrate that the proposed models can effectively identify features across a wide range of grayscale values in SEM images.
文摘A 3D crustal model was constructed using a combination of cutting-edge techniques,which were integrated to provide a density model for Egypt and address the sporadic distribution of seismic data.These techniques include obtaining gravity data from the Gravity Field and Steady-State Ocean Circulation Explorer(GOCE),creating seismic profiles,analyzing the receiver functions of seismic data,obtaining information from boreholes,and providing geological interpretations.GOCE satellite gravity data were processed to construct a preliminary model based on nonlinear inversions of the data.A regional crustal thickness model was developed using receiver functions,seismic refraction profiles,and geological insights.The inverted model was validated using borehole data and compared with seismic estimates.The model exhibited strong consistency and revealed a correlation between crustal thickness,geology,and tectonics of Egypt.It showed that the shallowest depths of the Moho are located in the north along the Mediterranean Sea and in the eastern part along the Red Sea,reflecting an oceanic plate with a thin,high-density crust.The deepest Moho depths are located in the southwestern part of Egypt,Red Sea coastal mountains,and Sinai Peninsula.The obtained 3D model of crustal thickness provided finely detailed Moho depth estimates that aligned closely with geology and tectonic characteristics of Egypt,contributing valuable insights into the subsurface structure and tectonic processes of region.
基金National Natural Science Foundation of China(No.51705545)。
文摘The active sound absorption technique excels in mitigating low-frequency sound waves,yet it falls short when dealing with medium and high-frequency sound waves.To enhance the sound-absorbing effect of medium and high-frequency sound waves,a novel semi-active sound absorption method has been introduced.This method modulates the surface impedance of a loudspeaker positioned behind the sound-absorbing material,thereby altering the sound absorption coefficient.The theoretical sound absorption coefficient is calculated using MATLAB and compared with the experimental one.Results show that the method can effectively modulates the absorption coefficient in response to varying incident sound wave frequencies,ensuring that it remains at its peak value.
基金funded by the Technology Funding Scheme of China Construction Second Engineering Bureau LTD(2020ZX150002)the National Natural Science Foundation Project of China(12262018).
文摘To address the challenges posed by tunnel construction in the alpine region,silica fume mixed concrete is commonly used as a construction material.The correlation between silica fume content and the lining life requires immediate investigation.In view of this phenomenon,the durability of unit lining concrete is predicted by analyzing three key indicators:carbonation depth,relative dynamic elastic modulus,and residual quality.This prediction is achieved by integrating the Entropy Weight Method,Grey theory life prediction model and BP artificial neural networks using data from tests and predictions of these indicators.Then,the Entropy Weight-Grey theory-BP Network Model is compared with other methods to analyze the predicted life.Finally,verify the sci-entificity of this model,and the optimum silica fume content of unit concrete lining is verified.The results showed,1)The addition of silica fume will accelerate the carbonization of unit concrete lining,and slow down the freeze-thaw cycle and sulfate erosion.2)The utilization of artificial neural networks is essential for enhancing the realism of the data,as it emphasizes the significance of silica fume content.3)Silica fume content of 10%results in the longest life and is the most suitable for lining construction.4)A comparison between single-factor and multi-factor predictions indicates that the multi-factor approach yields a longer maximum life.This improvement can be attributed to the inclusion of additional factors,such as freeze-thaw cycles and carbonation,which enhance the predicted life when employing these methods.In conclusion,the Entropy Weight-Grey Theory-BP Network life prediction Model is well-suited for tunnel lining in the alpine sulfate area of northwest China.
基金Supported by Nanchang High-Level Scientific and Technological Innovation Talents‘Double Hundred Plan’Project,China,No.2022-312.
文摘Rectal neuroendocrine tumor(rNET)is an indolent malignancy often detected during colonoscopy screening.The incidence of rNET has increased approximately 10-fold over the past 30 years.Most rNETs detected during screening endoscopy are small,measuring<10 mm.Current guidelines recommend endoscopic resection for small,well-differentiated rNET using modified endoscopic submucosal resection(mEMR)or endoscopic submucosal dissection.However,the optimal endoscopic treatment method remains uncertain.This paper summarizes the evidence on mEMR with submucosal stretching,mEMR without submucosal stretching,endoscopic submucosal dissection and endoscopic full-thickness resection.Given that rNETs often exhibit submucosal invasion,achieving adequate resection depth is crucial to ensure histological complete resection.mEMR with submucosal stretching appears favorable due to its high rate of histological complete resection,safety and convenience.Risk factors associated with lymph node and distant metastases are also discussed.A treatment algorithm is proposed to facilitate clinical decision-making.
文摘A new type of 785 nm semiconductor laser device has been proposed.The thin cladding and mode expansion layer structure incorporated into the epitaxy on the p-side significantly impacts the regulation of grating etching depth.Thinning of the p-side waveguide layer makes the light field bias to the n-side cladding layer.By coordinating the confinement effect of the cladding layer,the light confinement factor on the p-side is regulated.On the other hand,the introduction of a mode expansion layer facilitates the expansion of the mode profile on the p side cladding layer.Both these factors contribute positively to reducing the grating etching depth.Compared to the reported epitaxial structures of symmetric waveguides,the new structure significantly reduces the etching depth of the grating while ensuring adequate reflection intensity and maintaining resonance.Moreover,to improve the output performance of the device,the new epitaxial structure has been optimized.Based on the traditional epitaxial structure,an energy release layer and an electron blocking layer are added to improve the electronic recombination efficiency.This improved structure has an output performance comparable to that of a symmetric waveguide,despite being able to have a smaller gain area.
基金Supported by the National Natural Science Foundation of China(Nos.91858213,41776057,41761134051)part of the PhD work of O J AKINRINADE and the National Key Research and Development Program of China(Nos.2023 YFF 0803400,2023 YFF 0803404)。
文摘Based on Moho and Curie depth,heat flow,and upper mantle S-wave velocity anomaly,we infer the thermo-chemical structure of the lithospheres in Africa and surrounding oceans.The Moho depth is derived from gravity anomaly using the Parker-Oldenburg method,with constraints from seismic Moho.Crustal stratification defined by Curie-Moho depth difference shows that thermal and strong compositional processes may have shaped the lithospheric architecture of the African continental plate.Moho and Curie depths indicate the southern and eastern African cratons have thermochemical structures different from the West African Craton.Large Curie-Moho depth difference in southern and eastern Africa aligns with the low velocity anomaly originated from the core-mantle boundary.Mantle upwelling from the African low-velocity anomaly presumably induced partial melting at great depth,and the release of mineral-rich fluid and large amounts of volatile components facilitates a regional metasomatism,and results in a depleted,predominantly felsic,low-density paramagnetic crust.Mantle xenolith in kimberlites and volcanic rocks supports metasomatism by melts transmitted through narrow conduits as an intermittent or continuous upward flux of mineral-rich fluid.Alignment of the Curie-Moho depth difference at the intra-plate volcanic province correlates with weak lithospheric strength along the corridor connecting the intra-plate volcanic province with the Ethiopian plateau,suggesting a pathway for thermochemical asthenospheric flow.Crustal stratification and compositional-driven density layering support crustal buoyancy and uplift in the Hoggar,and southern and eastern Africa.A magnetized uppermost mantle is prevalent in the entire oceanic region,except at large igneous provinces(LIPs),volcanic seamounts,and oceanic plateaus,which have partial paramagnetic crusts.Our results support thermochemical upwelling related to the low velocity anomaly beneath the African plate.
