Electrochemical liquid lithium extraction technology has attracted much attention because of its high selectivity,good efficiency,and eco-friendliness.However,the low energy density per unit area and poor stability of...Electrochemical liquid lithium extraction technology has attracted much attention because of its high selectivity,good efficiency,and eco-friendliness.However,the low energy density per unit area and poor stability of traditional thin film electrodes(F-LMO),as well as manganese dissolution loss induced by the Jahn-Teller distortion of LiMn_(2)O_(4),hinder their industrial scalability.Herein,a durable and high-efficiency multistage porous LiMn_(2)O_(4) thick electrode was prepared sustainably by 3D printing technology(3DPLMO)for enhancing lithium recovery from salt lake brine.The multistage porous structure reduced the mass transfer resistance and shortened the ion diffusion path,which was conducive to accelerating the diffusion rate of Li+.Simultaneously,the three-dimensional conductive networks composed of reduced graphene oxide(r GO)and carbon nanotubes(CNT)synergized with the multistage pores effectively weakened the polarization phenomenon of the electrode and improved the stability of 3DP-LMO.The3DP-LMO exhibited a 5.5-fold higher extraction capacity per unit area and the Mn dissolution loss rate was only 1/15 compared with the F-LMO.Notably,the capacity retention rate of 3DP-LMO was 87.6%,significantly better than that of F-LMO(66.3%).Based on the quasi-in situ X-ray Diffraction results,the mechanism of lithium intercalation and deintercalation in 3DP-LMO was elucidated.Furthermore,lithium extraction parameters were optimized using response surface method-center composite design(RSM-CCD),resulting in an increase in lithium extraction capacity to 15.66 mg g^(-1)and a reduction in energy consumption to only 12.33 Wh mol^(-1).The results show that 3DP-LMO has significantly improved lithium extraction performance and stability,and has considerable prospects in practical application.展开更多
Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and...Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and biosafety concerns.In this study,we propose a high-precision automated colony extraction and separation system that combines large-field imaging and artificial intelligence(AI)to facilitate intelligent screening and localization of colonies.Firstly,a large-field imaging system was developed to capture high-resolution images of 90 mm Petri dishes,achieving a physical resolution of 13.2μm and an imaging speed of 13 frames per second.Subsequently,AI technology was employed for the automatic recognition and localiza-tion of colonies,enabling the selection of target colonies with diameters ranging from 1.9 to 2.3 mm.Next,a three-axis motion control platform was designed,accompanied by a path planning algorithm for the efficient extraction of colonies.An electronic pipette was employed for accurate colony collection.Additionally,a bacterial suspension concentration measurement module was developed,incorporating a 650 nm laser diode as the light source,achieving a measurement accuracy of 0.01 McFarland concentration(MCF).Finally,the system’s performance was validated through the preparation of an Esckerichia coli(E.coli)suspension.After 17 hours of cultivation,E.coli was extracted four times,achieving the target concentration set by the system.This work is expected to enable rapid and accurate microbial sample preparation,significantly reducing de-tection cycles and alleviating the workload of healthcare personnel.展开更多
Under the strategic framework of rural revitalization and agricultural modernization, Xinjiashan Specialty Coffee Base, located in Zaotang Village, Lujiang Town, Longyang District, Baoshan City, has been proactively i...Under the strategic framework of rural revitalization and agricultural modernization, Xinjiashan Specialty Coffee Base, located in Zaotang Village, Lujiang Town, Longyang District, Baoshan City, has been proactively investigating innovative models for agricultural development. Through extensive communication and collaboration, this base has established close partnerships with research institutions including Kunming University of Science and Technology, Baoshan University, and Yunnan Academy of Agricultural Sciences, with a commitment to thoroughly exploring the potential for resource recycling and ecological complementarity. An innovative four-in-one three-dimensional integrated planting system incorporating "coffee, bananas, green manure, and bees" has been implemented. Concurrently, technological and digital management strategies have been comprehensively integrated to improve planting efficiency. Under this model, the proportion of specialty coffee attains 71%, and the per-unit yield is 17% greater than that of the conventional planting model. This approach not only substantially enhances economic returns but also promotes the integrated development of ecological and social benefits, offering a valuable practical example and experiential reference for the specialty and sustainable advancement of the coffee industry in comparable regions.展开更多
Aerial surveys are dynamic and continuous processes,and there are different height distributions of the ground in the measurement area,which leads to problems such as overlapping measurement areas and inaccurate altit...Aerial surveys are dynamic and continuous processes,and there are different height distributions of the ground in the measurement area,which leads to problems such as overlapping measurement areas and inaccurate altitude correction during the survey process.Commonly used terrain correction methods are based on the concept of finite elementization of ground surface radioactive sources,using GPS coordinates,radar altitude,and ground elevation distribution information from aerial surveys,combined with the sourceless efficiency calibration method to construct a response matrix,which is then inverted for surface nuclide content.However,most of the sourceless efficiency calibration methods used are numerical calculations that consider the body detector as a point detector and do not consider the changes in intrinsic detection efficiency under different incident directions of gamma rays.Therefore,when the altitude of the measurement area varies significantly or the flight altitude of the aerial survey is relatively low,such sourceless efficiency calibration method calculations tend to have a large bias,which affects the accuracy of the terrain correction.To address the above problems,this study employs a novel sourceless efficiency calibration method based on the Boolean operation of the ray deposition process and simplifies the traditional body source measurement model to a surface source measurement model to achieve fast and accurate efficiency calibration.Then,through the discretization of the measurement process,the static measurement process is superposed as equivalent to the dynamic measurement process,and the dynamic measurement response matrix is built and optimized based on the calibration method.Finally,the PSO-MLEM algorithm was used to solve the dynamic measurement response matrix to achieve dynamic terrain correction of aerial survey data.Analysis of the Baiyun'ebo test area revealed that,after applying dynamic terrain correction,the inverted anomalies in uranium(eU),thorium(eTh),and potassium(K)concentrations were closer to ground measurements(within 5.72%-30.79%)and exhibited clearer anomaly boundaries compared to traditional height-based corrections.However,owing to the inherent statistical fluctuations and characteristics of matrix inversion,higher measurement values tend to absorb lower ones,potentially enlarging the anomalous regions.Nevertheless,the highanomaly regions after inversion largely coincided with the ground truth validation,demonstrating that the proposed method can effectively correct airborne gamma spectrometry data.展开更多
The lack of macro-continuity and mechanical strength of covalent organic frameworks(COFs)has significantly limited their practical applications.Here,we propose an“alcohol-triggered defect cleavage”strategy to precis...The lack of macro-continuity and mechanical strength of covalent organic frameworks(COFs)has significantly limited their practical applications.Here,we propose an“alcohol-triggered defect cleavage”strategy to precisely regulate the growth and stacking of COF grains through a moderate reversed Schiff base reaction,realizing the direct synthesis of COF nanofibers(CNFs)with high aspect ratio(L/D=103.05)and long length(>20μm).An individual CNF exhibits a biomimetic scale-like architecture,achieving superior flexibility and fatigue resistance under dynamic bending via a multiscale stress dissipation mechanism.Taking advantages of these structural features,we engineer CNF aerogels(CNF-As)with programmable porous structures(e.g.,honeycomb,lamellar,isotropic)via directional ice-template methodology.CNF-As demonstrate 100%COF content,high specific surface area(396.15 m^(2)g^(-1))and superelasticity(~0%elastic deformation after 500 compression cycles at 50%strain),outperforming most COF-based counterparts.Compared with the conventional COF aerogels,the unique structural features of CNF-A enable it to perform outstandingly in uranium extraction,with an 11.72-fold increment in adsorption capacity(920.12 mg g^(-1))and adsorption rate(89.9%),and a 2.48-fold improvement in selectivity(U/V=2.31).This study provides a direct strategy for the development of next-generation COF materials with outstanding functionality and structural robustness.展开更多
N,N,N',N'-tetraoctyl diglycolamide(TODGA)is a potential extractant for the co-extraction of lanthanides and actinides in high-level liquid waste.In this study,the radiolysis and extraction properties of TODGA ...N,N,N',N'-tetraoctyl diglycolamide(TODGA)is a potential extractant for the co-extraction of lanthanides and actinides in high-level liquid waste.In this study,the radiolysis and extraction properties of TODGA in kerosene solvents contacted with the aqueous phase of varying HNO_(3) concentrations were systematically investigated,and the complexation mechanism was analyzed in conjunction with density functional theory(DFT)calculations.After γ-irradiation,the variation of TODGA concentration was detected,and the variation trends in the relative content of radiolysis products(RPs)with sample type and absorbed dose were demonstrated.Results indicated that the breaking of the amide bond,ether bond,and C_(amide)-C_(ether)bond was the primary radiolysis routes.The aqueous-phase precipitate was studied as a potential new mode of TODGA radiolysis in ultrapure water aqueous phase.Moreover,TODGA/kerosene exhibited excellent extraction capabilities for lanthanides even after absorbing 100 kGy,and HNO_(3) can maintain a portion of TODGA's extraction capacity.The DFT method was applied to calculate and evaluate the complexing ability of TODGA and some of its RPs toward lanthanides.The results revealed that the complexing ability of TODGA for Ce(Ⅲ),Eu(Ⅲ),and Dy(Ⅲ)was enhanced successively,and the complexing ability of the RPs with intact oxygen-containing structures could not be neglected.展开更多
As an important class of phenanthroline derivatives containing soft N and hard O donor atoms,the laborious syntheses of unsymmetrical 1,10-phenanthroline-derived diamide ligands(DAPhen) have hindered its extensive stu...As an important class of phenanthroline derivatives containing soft N and hard O donor atoms,the laborious syntheses of unsymmetrical 1,10-phenanthroline-derived diamide ligands(DAPhen) have hindered its extensive study.In this work,we first report a convenient synthetic method for the construction of DAPhen using Friedländer reaction by two facile steps(vs.previous 12 steps).A variety of DAPhen ligands are readily available,especially unsymmetrical ones,which give us a platform to systematically study the substituent effect on f-block elements extraction performance.The performance of unsymmetrical extractants is experimentally confirmed to falls between that of their corresponding symmetrical extractants by extracting UO_(2)^(2+) as the representative f-block element.This work provides a direct and versatile method to synthesize symmetrical and unsymmetrical DAPhen,which paves way for the investigations on their coordination properties with metal ions and other applications.展开更多
Text semantic extraction has been envisioned as a promising solution to improve the data transmission efficiency with the limited radio resources for the autonomous interactions among machines and things in the future...Text semantic extraction has been envisioned as a promising solution to improve the data transmission efficiency with the limited radio resources for the autonomous interactions among machines and things in the future sixth-generation(6G)wireless networks.In this paper,we propose a Chinese text semantic extraction model,namely T-Pointer,to improve the quality of semantic extraction by integrating the Transformer with the pointer-generator network.The proposed T-Pointer model consists of a semantic encoder and a semantic decoder.In the encoding stage,we use the multi-head attention mechanism of the Transformer to extract semantic features from the input Chinese text.In the decoding stage,we first use the Transformer to extract multi-level global text features.Then,we introduce the pointer-generator network model to directly copy the keyword information from the source text.The simulation results demonstrate that the T-Pointer model can improve the bilingual evaluation understudy(BLEU)and recalloriented understudy for gisting evaluation(ROUGE)by 14.69%and 14.87%on average in comparison with the state-of-the-art models,respectively.Also,we implement the T-Pointer model on a semantic communication system based on the universal software radio peripheral(USRP)platform.The result shows that the packet delay of semantic transmission can be reduced by 52.05%on average,compared to traditional information transmission.展开更多
This article presents a new synergistic extraction system composed of Cyanex 272(C272,bis(2,4,4-trimethylpentyl)phosphinic acid)and iso-octanol for Sc_(3+) separation.The proposed synergistic system possessed an Sc^(3...This article presents a new synergistic extraction system composed of Cyanex 272(C272,bis(2,4,4-trimethylpentyl)phosphinic acid)and iso-octanol for Sc_(3+) separation.The proposed synergistic system possessed an Sc^(3+) extraction efficiency of 93.5%and a back-extraction efficiency of 82.7%,with selectivity coefficients of β_(Sc/Fe)=459 and β_(Sc/Al)=4241,which are considerably higher as compared to the current extraction systems.The extraction mechanism was studied and interpreted.The enhanced extraction efficiency is attributed to the increased hydrophobicity of the ternary complex,whereas the back-extraction efficiency can be ascribed to the attenuated stability of the complex.C272 and C272–iso-octanol systems also possess considerable surface activity,which is beneficial for the phase separation in solvent extraction.Based on the solvent extraction results,a preliminary study was conducted on polymer inclusion membranes(PIMs)using the binary system for Sc^(3+) separation to avoid the formation of the third phase,achieving an optimal initial flux of PIM of 6.71×10^(−4)mol·m^(−2)·h^(−1).Our results provide valuable information on highly efficient Sc^(3+) separation,and the study on PIM extraction has shown a green alternative to solvent extraction.展开更多
The extraction of uranium from seawater via membrane adsorption is a promising strategy for ensuring a long-term supply of uranium and the sustainability of nuclear energy.However,this approach has been hindered by th...The extraction of uranium from seawater via membrane adsorption is a promising strategy for ensuring a long-term supply of uranium and the sustainability of nuclear energy.However,this approach has been hindered by the longstanding challenge of identifying sustainable membrane materials.In response,we propose a prototypal hybridization strategy to design a novel series of aminated conjugated microporous polymer(CMPN)@collagen fiber membrane(COLM).These sustainable and low-cost membrane materials allow a rapid and high-affinity kinetic to capture 90%of the uranium in just 30 min from 50 ppm with a high selectivity of Kd>105 mL·g^(−1).They also afford a robustly reusable adsorption capacity as high as 345 mg·g^(−1)that could harvest 1.61 mg·g^(−1)of uranium in a short 7-day real marine engineering in Fujian Province,even though suffered from very low uranium concentration of 3.29μg·L^(−1)and tough influence of salts such as 10.77 g·L^(−1)of Na^(+),1.75μg·L^(−1)of VO_(3)^(−)etc.in the rough seas.The structural evidence from both experimental and theoretical studies confirmed the formation of favorable chelating motifs from the amino group on CMPN-COLM,and the intensification by the synergistic effect from the size-sieving action of CMPN and the capillary inflow effect of COLM.展开更多
Deep learning has made significant progress in the field of oriented object detection for remote sensing images.However,existing methods still face challenges when dealing with difficult tasks such as multi-scale targ...Deep learning has made significant progress in the field of oriented object detection for remote sensing images.However,existing methods still face challenges when dealing with difficult tasks such as multi-scale targets,complex backgrounds,and small objects in remote sensing.Maintaining model lightweight to address resource constraints in remote sensing scenarios while improving task completion for remote sensing tasks remains a research hotspot.Therefore,we propose an enhanced multi-scale feature extraction lightweight network EM-YOLO based on the YOLOv8s architecture,specifically optimized for the characteristics of large target scale variations,diverse orientations,and numerous small objects in remote sensing images.Our innovations lie in two main aspects:First,a dynamic snake convolution(DSC)is introduced into the backbone network to enhance the model’s feature extraction capability for oriented targets.Second,an innovative focusing-diffusion module is designed in the feature fusion neck to effectively integrate multi-scale feature information.Finally,we introduce Layer-Adaptive Sparsity for magnitude-based Pruning(LASP)method to perform lightweight network pruning to better complete tasks in resource-constrained scenarios.Experimental results on the lightweight platform Orin demonstrate that the proposed method significantly outperforms the original YOLOv8s model in oriented remote sensing object detection tasks,and achieves comparable or superior performance to state-of-the-art methods on three authoritative remote sensing datasets(DOTA v1.0,DOTA v1.5,and HRSC2016).展开更多
Since Google introduced the concept of Knowledge Graphs(KGs)in 2012,their construction technologies have evolved into a comprehensive methodological framework encompassing knowledge acquisition,extraction,representati...Since Google introduced the concept of Knowledge Graphs(KGs)in 2012,their construction technologies have evolved into a comprehensive methodological framework encompassing knowledge acquisition,extraction,representation,modeling,fusion,computation,and storage.Within this framework,knowledge extraction,as the core component,directly determines KG quality.In military domains,traditional manual curation models face efficiency constraints due to data fragmentation,complex knowledge architectures,and confidentiality protocols.Meanwhile,crowdsourced ontology construction approaches from general domains prove non-transferable,while human-crafted ontologies struggle with generalization deficiencies.To address these challenges,this study proposes an OntologyAware LLM Methodology for Military Domain Knowledge Extraction(LLM-KE).This approach leverages the deep semantic comprehension capabilities of Large Language Models(LLMs)to simulate human experts’cognitive processes in crowdsourced ontology construction,enabling automated extraction of military textual knowledge.It concurrently enhances knowledge processing efficiency and improves KG completeness.Empirical analysis demonstrates that this method effectively resolves scalability and dynamic adaptation challenges in military KG construction,establishing a novel technological pathway for advancing military intelligence development.展开更多
Currently,thyroid diseases are prevalent worldwide;therefore,it is necessary to develop techniques that help doctors improve their diagnostic skills for such diseases.In previous studies,2-dimensional convolutional ne...Currently,thyroid diseases are prevalent worldwide;therefore,it is necessary to develop techniques that help doctors improve their diagnostic skills for such diseases.In previous studies,2-dimensional convolutional neural network(2D CNN)techniques were employed to classify thyroid nodules as benign and malignant without detecting the presence of thyroid nodules in the obtained ultrasound images.To address this issue,we propose a 3-dimensional convolutional neural network(3D CNN)for thyroid nodule detection.The proposed CNN exploits the 3D information and spatial features contained in ultrasound images and generates distinctive features during its training using multiple samples,even for small nodules.In contrast,a 2D CNN only depends on spatial features.In this study,we used two datasets of 2210 ultrasound images obtained from the Sultan Abdul Aziz Shah Hospital in Malaysia,and a public open dataset,Digital Database Thyroid Image(DDTI).We created folders containing three images each,processed the images and extracted volumetric features suitable for the 3-dimensional convolutional neural network(3D CNN).The proposed model was assessed using four metrics:accuracy,recall,precision and F1 score.The results showed that the accuracy of the model in predicting the presence of thyroid nodules in ultrasound images was 96%.In conclusion,this study could help radiologists in hospitals and medical centres in classifying ultrasound images and detecting thyroid nodules.展开更多
According to the Mindlin plate theory and the first-order piston theory,this work obtains accurate closed-form eigensolutions for the flutter problem of three-dimensional(3D)rectangular laminated panels.The governing ...According to the Mindlin plate theory and the first-order piston theory,this work obtains accurate closed-form eigensolutions for the flutter problem of three-dimensional(3D)rectangular laminated panels.The governing differential equations are derived by the Hamilton's variational principle,and then solved by the iterative Separation-of-Variable(i SOV)method,which are applicable to arbitrary combinations of homogeneous Boundary Conditions(BCs).However,only the simply-support,clamped and cantilever panels are considered in this work for the sake of clarity.With the closed-form eigensolutions,the flutter frequency,flutter mode and flutter boundary are presented,and the effect of shear deformation and aerodynamic damping on flutter frequencies is investigated.Besides,the relation between panel energy and the work of aerodynamic load is discussed.The numerical comparisons reveal the following.(A)The flutter eigenvalues obtained by the present method are accurate,validated by the Finite Element Method(FEM)and the Galerkin method.(B)When the span-chord ratio is larger than 3,simplifying a 3D panel to 2D(two-dimensional)panel is reasonable and the relative differences of the flutter points predicted by the two models are less than one percent.(C)The reciprocal relationship between the mechanical energy of the panel and the work done by aerodynamic load is verified by using the present flutter eigenvalues and modes,further indicating the high accuracy of the present solutions.(D)The coupling of shear deformation and aerodynamic damping prevents frequency coalescing.展开更多
Recovering LiFePO_(4) extraction slag(LES)-the FePO_(4)-rich residue formed after Li leaching from spent LiFePO_(4)-has become pivotal to minimizing resource losses,mitigating environmental risks,and advancing circula...Recovering LiFePO_(4) extraction slag(LES)-the FePO_(4)-rich residue formed after Li leaching from spent LiFePO_(4)-has become pivotal to minimizing resource losses,mitigating environmental risks,and advancing circularity in lithium-ion battery value chains.However,integrative frameworks that link closed-loop routes(returning to battery precursors/cathodes)with non-closed-loop upcycling are still limited,constraining process optimization and scale-up.This review synthesizes current progress in LES recycling with emphasis on maximizing recovery efficiency and product value.In closed-loop pathways,hydrometallurgical purification removes impurities to yield battery-grade FePO_(4) as an LiFePO_(4) precursor,while direct relithiation(e.g.,solid-state sintering aided by Li sources and reductants)restores Li and reduces Fe^(3+)to Fe^(2+),thereby regenerating LiFePO_(4) cathodes from LES.In non-closed-loop pathways,compositionally guided upcycling converts LES into advanced materials(e.g.,high-performance electrodes,highcapacity adsorbents),thereby broadening the techno-economic value propositions.We also distill lessons from early industrial practice,identifying constraints arising from feedstock variability,energy-cost coupling(thermal/chemical utilities),and product-quality assurance(battery-grade specifications).Finally,we map research directions-including data-driven feed characterization and process control,defecthealing relithiation strategies and interfacial engineering,quality grading and market pathways,and multi-scenario deployment-to enhance the technical and economic sustainability of LES recycling and accelerate its contribution to a circular battery economy.展开更多
To ease the scarcity of lithium(Li)resource and cut down on environmental pollution,an efficient,selective,inexpensive and sustainable Li recycling process from waste batteries is needed,which is yet to be achieved.He...To ease the scarcity of lithium(Li)resource and cut down on environmental pollution,an efficient,selective,inexpensive and sustainable Li recycling process from waste batteries is needed,which is yet to be achieved.Here,we report a low-potential photoelectrochemical(PEC)system that selectively and efficiently extracts Li metals from multi-cation electrolytes under 1 sun illumination.Based on the difference of redox potential,we can get rid of the disturbance of other cations(i.e.,Fe,Co and Ni ions)by a bias-free PEC device to realize the extraction of high-purity Li metals on a coplanar Si-based photocathode-TiO_(2) photoanode tandem device at 2 V of applied bias(far less than the redox potentials of Li^(+)/Li).In such system,the extraction rate of Li metals(purity>99.5%)exceeds 1.35 g h^(-1)m^(-2)with 90%of Faradaic efficiency.Long-term experiments,different electrode/electrolyte tests,and various price assessments further demonstrate the stability,compatibility and economy of PEC extraction system,enabling a solar-driven pathway for the recycling of critical metal resources.展开更多
As a key low-carbon energy source,nuclear power plays a vital role in the global transition toward sustainable energy.Photocatalytic uranium extraction from seawater(UES)offers a promising solution to ensure long-term...As a key low-carbon energy source,nuclear power plays a vital role in the global transition toward sustainable energy.Photocatalytic uranium extraction from seawater(UES)offers a promising solution to ensure long-term uranium supply but is challenged by ultra-low uranium concentrations and ion interference.To overcome these issues,we design three diketopyrrolopyrrole-based covalent organic frameworks(COFs)via a synergisticπ-extended lock and carboxyl-functionalized anchor molecular engineering strategy.Among them,TPy-DPP-COF features a covalently lockedπ-conjugated structure that enhances planarity,optimizes energy alignment,and minimizes exciton binding energy,thereby promoting charge transfer and suppressing recombination.Concurrently,carboxyl groups enable uranyl-specific coordination and create local electric fields to facilitate charge separation.These features contribute to the outstanding performance of TPy-DPP-COF,which achieves a high uranium adsorption capacity of 16.33 mg g−1 in natural seawater under irradiation,with only 29.3%capacity loss after 10 cycles,surpassing industrial benchmarks.Density functional theory(DFT)calculations and experimental studies reveal a synergistic photocatalysis-adsorption pathway,with DPP units acting as active sites for uranium reduction.This work highlights a molecular design strategy for developing efficient COF-based photocatalysts for practical marine uranium recovery.展开更多
AIM:To investigate the long-term outcomes in acute primary angle closure(APAC)patients treated with lens extraction(LE)surgery and to identify risk factors for glaucomatous optic neuropathy(GON).METHODS:In this longit...AIM:To investigate the long-term outcomes in acute primary angle closure(APAC)patients treated with lens extraction(LE)surgery and to identify risk factors for glaucomatous optic neuropathy(GON).METHODS:In this longitudinal observational study,detailed medical histories of APAC patients and comprehensive ophthalmic examinations at final followup were collected.Logistic regression analysis was performed to identify predictors of blindness.Univariate and multivariate linear regression analyses were conducted to determine risk factors associated with visual outcomes.RESULTS:This study included 39 affected eyes of 31 subjects(26 females)with an average age of 74.1±8.0y.At 6.7±4.2y after APAC attack,2(5.7%)eyes had bestcorrected visual acuity(VA)worse than 3/60.Advanced glaucomatous visual field loss was observed in 15(39.5%)affected eyes and 5(25.0%)fellow eyes.Nine affected eyes(23.7%)had GON,and 11(28.9%)were blind.Six(15.4%)affected eyes and 2(9.1%)fellow eyes had suspicious progression.A significantly higher blindness rate in factory workers compared to office workers.Logistic regression identified that worse VA at attack(OR 10.568,95%CI 1.288-86.695;P=0.028)and worse early postoperative VA(OR 13.214,95%CI 1.157-150.881;P=0.038)were risk factors for blindness.Multivariate regression showed that longer duration of elevated intraocular pressure(P=0.004)and worse early postoperative VA(P=0.009)were associated with worse visual outcomes.CONCLUSION:Despite LE surgery,some APAC patients experience continued visual function deterioration.Lifelong monitoring is necessary.Target pressure and progression rates should be re-evaluated during follow-up.展开更多
Discontinuity traces significantly impact the mechanical properties of rock masses,making their rapid and accurate identification crucial for stability analysis.We propose a framework using the multi-scale surface var...Discontinuity traces significantly impact the mechanical properties of rock masses,making their rapid and accurate identification crucial for stability analysis.We propose a framework using the multi-scale surface variation index(MsSVI)and transfer-learning enhanced artificial neural network(ANN)for efficient discontinuity trace extraction from rock mass point clouds.Leveraging the similarity between regular geometric bodies and engineering rock masses,we extract trace feature points without manual threshold selection.Our contributions include:(1)An adaptive radius MsSVI calculation method based on density information;(2)a universal trace feature point classification model trained using MsSVI and ANN via inductive transfer learning;and(3)a random sampling L1-medial skeleton algorithm for precise trace feature point extraction,bypassing point cloud triangulation.Experimental results show that our model achieves a 90.2%F1-score on test sets,demonstrating its accuracy and robustness.Furthermore,our method excels in trace detail extraction on two datasets,surpassing existing models and highlighting its potential for rock mass structural analysis.展开更多
In the last two decades,significant research has been conducted in the field of automated extraction of rock mass discontinuity characteristics from three-dimensional(3D)models.This provides several methodologies for ...In the last two decades,significant research has been conducted in the field of automated extraction of rock mass discontinuity characteristics from three-dimensional(3D)models.This provides several methodologies for acquiring discontinuity measurements from 3D models,such as point clouds generated using laser scanning or photogrammetry.However,even with numerous automated and semiautomated methods presented in the literature,there is not one single method that can automatically characterize discontinuities accurately in a minimum of time.In this paper,we critically review all the existing methods proposed in the literature for the extraction of discontinuity characteristics such as joint sets and orientations,persistence,joint spacing,roughness and block size using point clouds,digital elevation maps,or meshes.As a result of this review,we identify the strengths and drawbacks of each method used for extracting those characteristics.We found that the approaches based on voxels and region growing are superior in extracting joint planes from 3D point clouds.Normal tensor voting with trace growth algorithm is a robust method for measuring joint trace length from 3D meshes.Spacing is estimated by calculating the perpendicular distance between joint planes.Several independent roughness indices are presented to quantify roughness from 3D surface models,but there is a need to incorporate these indices into automated methodologies.There is a lack of efficient algorithms for direct computation of block size from 3D rock mass surface models.展开更多
基金supported by the National Key R&D Program of China(No.2022YFE0208300)the National Natural Science Foundation of China(No.22278426)+2 种基金the China National Funds for Distinguished Young Scientists(No.22425808)the China Postdoctoral Science Foundation(No.2025M771155)the Science Foundation of China University of Petroleum,Beijing(Nos.2462024XKBH001,2462022YJRC003,2462022YJRC002,2462025BJRC002)。
文摘Electrochemical liquid lithium extraction technology has attracted much attention because of its high selectivity,good efficiency,and eco-friendliness.However,the low energy density per unit area and poor stability of traditional thin film electrodes(F-LMO),as well as manganese dissolution loss induced by the Jahn-Teller distortion of LiMn_(2)O_(4),hinder their industrial scalability.Herein,a durable and high-efficiency multistage porous LiMn_(2)O_(4) thick electrode was prepared sustainably by 3D printing technology(3DPLMO)for enhancing lithium recovery from salt lake brine.The multistage porous structure reduced the mass transfer resistance and shortened the ion diffusion path,which was conducive to accelerating the diffusion rate of Li+.Simultaneously,the three-dimensional conductive networks composed of reduced graphene oxide(r GO)and carbon nanotubes(CNT)synergized with the multistage pores effectively weakened the polarization phenomenon of the electrode and improved the stability of 3DP-LMO.The3DP-LMO exhibited a 5.5-fold higher extraction capacity per unit area and the Mn dissolution loss rate was only 1/15 compared with the F-LMO.Notably,the capacity retention rate of 3DP-LMO was 87.6%,significantly better than that of F-LMO(66.3%).Based on the quasi-in situ X-ray Diffraction results,the mechanism of lithium intercalation and deintercalation in 3DP-LMO was elucidated.Furthermore,lithium extraction parameters were optimized using response surface method-center composite design(RSM-CCD),resulting in an increase in lithium extraction capacity to 15.66 mg g^(-1)and a reduction in energy consumption to only 12.33 Wh mol^(-1).The results show that 3DP-LMO has significantly improved lithium extraction performance and stability,and has considerable prospects in practical application.
文摘Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and biosafety concerns.In this study,we propose a high-precision automated colony extraction and separation system that combines large-field imaging and artificial intelligence(AI)to facilitate intelligent screening and localization of colonies.Firstly,a large-field imaging system was developed to capture high-resolution images of 90 mm Petri dishes,achieving a physical resolution of 13.2μm and an imaging speed of 13 frames per second.Subsequently,AI technology was employed for the automatic recognition and localiza-tion of colonies,enabling the selection of target colonies with diameters ranging from 1.9 to 2.3 mm.Next,a three-axis motion control platform was designed,accompanied by a path planning algorithm for the efficient extraction of colonies.An electronic pipette was employed for accurate colony collection.Additionally,a bacterial suspension concentration measurement module was developed,incorporating a 650 nm laser diode as the light source,achieving a measurement accuracy of 0.01 McFarland concentration(MCF).Finally,the system’s performance was validated through the preparation of an Esckerichia coli(E.coli)suspension.After 17 hours of cultivation,E.coli was extracted four times,achieving the target concentration set by the system.This work is expected to enable rapid and accurate microbial sample preparation,significantly reducing de-tection cycles and alleviating the workload of healthcare personnel.
文摘Under the strategic framework of rural revitalization and agricultural modernization, Xinjiashan Specialty Coffee Base, located in Zaotang Village, Lujiang Town, Longyang District, Baoshan City, has been proactively investigating innovative models for agricultural development. Through extensive communication and collaboration, this base has established close partnerships with research institutions including Kunming University of Science and Technology, Baoshan University, and Yunnan Academy of Agricultural Sciences, with a commitment to thoroughly exploring the potential for resource recycling and ecological complementarity. An innovative four-in-one three-dimensional integrated planting system incorporating "coffee, bananas, green manure, and bees" has been implemented. Concurrently, technological and digital management strategies have been comprehensively integrated to improve planting efficiency. Under this model, the proportion of specialty coffee attains 71%, and the per-unit yield is 17% greater than that of the conventional planting model. This approach not only substantially enhances economic returns but also promotes the integrated development of ecological and social benefits, offering a valuable practical example and experiential reference for the specialty and sustainable advancement of the coffee industry in comparable regions.
基金supported by the National Key Research and Development Program(No.2022YFC2807400)the National Natural Science Foundation of China(Nos.12265003 and 12205044)。
文摘Aerial surveys are dynamic and continuous processes,and there are different height distributions of the ground in the measurement area,which leads to problems such as overlapping measurement areas and inaccurate altitude correction during the survey process.Commonly used terrain correction methods are based on the concept of finite elementization of ground surface radioactive sources,using GPS coordinates,radar altitude,and ground elevation distribution information from aerial surveys,combined with the sourceless efficiency calibration method to construct a response matrix,which is then inverted for surface nuclide content.However,most of the sourceless efficiency calibration methods used are numerical calculations that consider the body detector as a point detector and do not consider the changes in intrinsic detection efficiency under different incident directions of gamma rays.Therefore,when the altitude of the measurement area varies significantly or the flight altitude of the aerial survey is relatively low,such sourceless efficiency calibration method calculations tend to have a large bias,which affects the accuracy of the terrain correction.To address the above problems,this study employs a novel sourceless efficiency calibration method based on the Boolean operation of the ray deposition process and simplifies the traditional body source measurement model to a surface source measurement model to achieve fast and accurate efficiency calibration.Then,through the discretization of the measurement process,the static measurement process is superposed as equivalent to the dynamic measurement process,and the dynamic measurement response matrix is built and optimized based on the calibration method.Finally,the PSO-MLEM algorithm was used to solve the dynamic measurement response matrix to achieve dynamic terrain correction of aerial survey data.Analysis of the Baiyun'ebo test area revealed that,after applying dynamic terrain correction,the inverted anomalies in uranium(eU),thorium(eTh),and potassium(K)concentrations were closer to ground measurements(within 5.72%-30.79%)and exhibited clearer anomaly boundaries compared to traditional height-based corrections.However,owing to the inherent statistical fluctuations and characteristics of matrix inversion,higher measurement values tend to absorb lower ones,potentially enlarging the anomalous regions.Nevertheless,the highanomaly regions after inversion largely coincided with the ground truth validation,demonstrating that the proposed method can effectively correct airborne gamma spectrometry data.
基金supported by the National Natural Science Foundation of China(No.52403035)the Shanghai Sailing Program(23YF1400300)+1 种基金the Fundamental Research Funds for the Central Universities(2232023D-05)the Weiqiao Teaching and Research Innovation Program.
文摘The lack of macro-continuity and mechanical strength of covalent organic frameworks(COFs)has significantly limited their practical applications.Here,we propose an“alcohol-triggered defect cleavage”strategy to precisely regulate the growth and stacking of COF grains through a moderate reversed Schiff base reaction,realizing the direct synthesis of COF nanofibers(CNFs)with high aspect ratio(L/D=103.05)and long length(>20μm).An individual CNF exhibits a biomimetic scale-like architecture,achieving superior flexibility and fatigue resistance under dynamic bending via a multiscale stress dissipation mechanism.Taking advantages of these structural features,we engineer CNF aerogels(CNF-As)with programmable porous structures(e.g.,honeycomb,lamellar,isotropic)via directional ice-template methodology.CNF-As demonstrate 100%COF content,high specific surface area(396.15 m^(2)g^(-1))and superelasticity(~0%elastic deformation after 500 compression cycles at 50%strain),outperforming most COF-based counterparts.Compared with the conventional COF aerogels,the unique structural features of CNF-A enable it to perform outstandingly in uranium extraction,with an 11.72-fold increment in adsorption capacity(920.12 mg g^(-1))and adsorption rate(89.9%),and a 2.48-fold improvement in selectivity(U/V=2.31).This study provides a direct strategy for the development of next-generation COF materials with outstanding functionality and structural robustness.
文摘N,N,N',N'-tetraoctyl diglycolamide(TODGA)is a potential extractant for the co-extraction of lanthanides and actinides in high-level liquid waste.In this study,the radiolysis and extraction properties of TODGA in kerosene solvents contacted with the aqueous phase of varying HNO_(3) concentrations were systematically investigated,and the complexation mechanism was analyzed in conjunction with density functional theory(DFT)calculations.After γ-irradiation,the variation of TODGA concentration was detected,and the variation trends in the relative content of radiolysis products(RPs)with sample type and absorbed dose were demonstrated.Results indicated that the breaking of the amide bond,ether bond,and C_(amide)-C_(ether)bond was the primary radiolysis routes.The aqueous-phase precipitate was studied as a potential new mode of TODGA radiolysis in ultrapure water aqueous phase.Moreover,TODGA/kerosene exhibited excellent extraction capabilities for lanthanides even after absorbing 100 kGy,and HNO_(3) can maintain a portion of TODGA's extraction capacity.The DFT method was applied to calculate and evaluate the complexing ability of TODGA and some of its RPs toward lanthanides.The results revealed that the complexing ability of TODGA for Ce(Ⅲ),Eu(Ⅲ),and Dy(Ⅲ)was enhanced successively,and the complexing ability of the RPs with intact oxygen-containing structures could not be neglected.
基金financial support from the National Natural Science Foundation of China (Nos.22476178,U2067213)Natural Science Foundation of Zhejiang Province (No.LRG25B060002)。
文摘As an important class of phenanthroline derivatives containing soft N and hard O donor atoms,the laborious syntheses of unsymmetrical 1,10-phenanthroline-derived diamide ligands(DAPhen) have hindered its extensive study.In this work,we first report a convenient synthetic method for the construction of DAPhen using Friedländer reaction by two facile steps(vs.previous 12 steps).A variety of DAPhen ligands are readily available,especially unsymmetrical ones,which give us a platform to systematically study the substituent effect on f-block elements extraction performance.The performance of unsymmetrical extractants is experimentally confirmed to falls between that of their corresponding symmetrical extractants by extracting UO_(2)^(2+) as the representative f-block element.This work provides a direct and versatile method to synthesize symmetrical and unsymmetrical DAPhen,which paves way for the investigations on their coordination properties with metal ions and other applications.
基金National Natural Science Foundation of China under Grants 62122069,62071431,62072490,62301490Science and Technology Development Fund of Macao,Macao,China under Grant 0158/2022/A+2 种基金Guangdong Basic and Applied Basic Research Foundation(2022A1515011287)MYRG2020-00107-IOTSCFDCT SKL-IOTSC(UM)-2021-2023。
文摘Text semantic extraction has been envisioned as a promising solution to improve the data transmission efficiency with the limited radio resources for the autonomous interactions among machines and things in the future sixth-generation(6G)wireless networks.In this paper,we propose a Chinese text semantic extraction model,namely T-Pointer,to improve the quality of semantic extraction by integrating the Transformer with the pointer-generator network.The proposed T-Pointer model consists of a semantic encoder and a semantic decoder.In the encoding stage,we use the multi-head attention mechanism of the Transformer to extract semantic features from the input Chinese text.In the decoding stage,we first use the Transformer to extract multi-level global text features.Then,we introduce the pointer-generator network model to directly copy the keyword information from the source text.The simulation results demonstrate that the T-Pointer model can improve the bilingual evaluation understudy(BLEU)and recalloriented understudy for gisting evaluation(ROUGE)by 14.69%and 14.87%on average in comparison with the state-of-the-art models,respectively.Also,we implement the T-Pointer model on a semantic communication system based on the universal software radio peripheral(USRP)platform.The result shows that the packet delay of semantic transmission can be reduced by 52.05%on average,compared to traditional information transmission.
基金support from the National Natural Science Foundation of China Regional Innovation and Development Joint Fund(U24A20557)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDC0230403)+3 种基金the National Natural Science Foundation of China(22378393,22208356)“Hundred Talents Program”of the Chinese Academy of Sciencesthe Chinese Academy of Sciences stably supports the youth team plan in the field of basic research(YSBR 038)Key Research&Development projects in Qinghai Province(2023-HZ-805).
文摘This article presents a new synergistic extraction system composed of Cyanex 272(C272,bis(2,4,4-trimethylpentyl)phosphinic acid)and iso-octanol for Sc_(3+) separation.The proposed synergistic system possessed an Sc^(3+) extraction efficiency of 93.5%and a back-extraction efficiency of 82.7%,with selectivity coefficients of β_(Sc/Fe)=459 and β_(Sc/Al)=4241,which are considerably higher as compared to the current extraction systems.The extraction mechanism was studied and interpreted.The enhanced extraction efficiency is attributed to the increased hydrophobicity of the ternary complex,whereas the back-extraction efficiency can be ascribed to the attenuated stability of the complex.C272 and C272–iso-octanol systems also possess considerable surface activity,which is beneficial for the phase separation in solvent extraction.Based on the solvent extraction results,a preliminary study was conducted on polymer inclusion membranes(PIMs)using the binary system for Sc^(3+) separation to avoid the formation of the third phase,achieving an optimal initial flux of PIM of 6.71×10^(−4)mol·m^(−2)·h^(−1).Our results provide valuable information on highly efficient Sc^(3+) separation,and the study on PIM extraction has shown a green alternative to solvent extraction.
基金supported by National Natural Science Foundation of China(Grant No.22378066,22108040)Collaboration&Innovation Platform Project of National Independent Innovation Demonstration Zone(Fuzhou,Xiamen&Quanzhou)(Project No:3502ZCQXT2023004).
文摘The extraction of uranium from seawater via membrane adsorption is a promising strategy for ensuring a long-term supply of uranium and the sustainability of nuclear energy.However,this approach has been hindered by the longstanding challenge of identifying sustainable membrane materials.In response,we propose a prototypal hybridization strategy to design a novel series of aminated conjugated microporous polymer(CMPN)@collagen fiber membrane(COLM).These sustainable and low-cost membrane materials allow a rapid and high-affinity kinetic to capture 90%of the uranium in just 30 min from 50 ppm with a high selectivity of Kd>105 mL·g^(−1).They also afford a robustly reusable adsorption capacity as high as 345 mg·g^(−1)that could harvest 1.61 mg·g^(−1)of uranium in a short 7-day real marine engineering in Fujian Province,even though suffered from very low uranium concentration of 3.29μg·L^(−1)and tough influence of salts such as 10.77 g·L^(−1)of Na^(+),1.75μg·L^(−1)of VO_(3)^(−)etc.in the rough seas.The structural evidence from both experimental and theoretical studies confirmed the formation of favorable chelating motifs from the amino group on CMPN-COLM,and the intensification by the synergistic effect from the size-sieving action of CMPN and the capillary inflow effect of COLM.
基金funded by the Hainan Province Science and Technology Special Fund under Grant ZDYF2024GXJS292.
文摘Deep learning has made significant progress in the field of oriented object detection for remote sensing images.However,existing methods still face challenges when dealing with difficult tasks such as multi-scale targets,complex backgrounds,and small objects in remote sensing.Maintaining model lightweight to address resource constraints in remote sensing scenarios while improving task completion for remote sensing tasks remains a research hotspot.Therefore,we propose an enhanced multi-scale feature extraction lightweight network EM-YOLO based on the YOLOv8s architecture,specifically optimized for the characteristics of large target scale variations,diverse orientations,and numerous small objects in remote sensing images.Our innovations lie in two main aspects:First,a dynamic snake convolution(DSC)is introduced into the backbone network to enhance the model’s feature extraction capability for oriented targets.Second,an innovative focusing-diffusion module is designed in the feature fusion neck to effectively integrate multi-scale feature information.Finally,we introduce Layer-Adaptive Sparsity for magnitude-based Pruning(LASP)method to perform lightweight network pruning to better complete tasks in resource-constrained scenarios.Experimental results on the lightweight platform Orin demonstrate that the proposed method significantly outperforms the original YOLOv8s model in oriented remote sensing object detection tasks,and achieves comparable or superior performance to state-of-the-art methods on three authoritative remote sensing datasets(DOTA v1.0,DOTA v1.5,and HRSC2016).
文摘Since Google introduced the concept of Knowledge Graphs(KGs)in 2012,their construction technologies have evolved into a comprehensive methodological framework encompassing knowledge acquisition,extraction,representation,modeling,fusion,computation,and storage.Within this framework,knowledge extraction,as the core component,directly determines KG quality.In military domains,traditional manual curation models face efficiency constraints due to data fragmentation,complex knowledge architectures,and confidentiality protocols.Meanwhile,crowdsourced ontology construction approaches from general domains prove non-transferable,while human-crafted ontologies struggle with generalization deficiencies.To address these challenges,this study proposes an OntologyAware LLM Methodology for Military Domain Knowledge Extraction(LLM-KE).This approach leverages the deep semantic comprehension capabilities of Large Language Models(LLMs)to simulate human experts’cognitive processes in crowdsourced ontology construction,enabling automated extraction of military textual knowledge.It concurrently enhances knowledge processing efficiency and improves KG completeness.Empirical analysis demonstrates that this method effectively resolves scalability and dynamic adaptation challenges in military KG construction,establishing a novel technological pathway for advancing military intelligence development.
基金supported by the Ministry of Higher Education under the Fundamentals Research Grant Scheme(FRGS/1/2024/ICT02/UPM/02/5).
文摘Currently,thyroid diseases are prevalent worldwide;therefore,it is necessary to develop techniques that help doctors improve their diagnostic skills for such diseases.In previous studies,2-dimensional convolutional neural network(2D CNN)techniques were employed to classify thyroid nodules as benign and malignant without detecting the presence of thyroid nodules in the obtained ultrasound images.To address this issue,we propose a 3-dimensional convolutional neural network(3D CNN)for thyroid nodule detection.The proposed CNN exploits the 3D information and spatial features contained in ultrasound images and generates distinctive features during its training using multiple samples,even for small nodules.In contrast,a 2D CNN only depends on spatial features.In this study,we used two datasets of 2210 ultrasound images obtained from the Sultan Abdul Aziz Shah Hospital in Malaysia,and a public open dataset,Digital Database Thyroid Image(DDTI).We created folders containing three images each,processed the images and extracted volumetric features suitable for the 3-dimensional convolutional neural network(3D CNN).The proposed model was assessed using four metrics:accuracy,recall,precision and F1 score.The results showed that the accuracy of the model in predicting the presence of thyroid nodules in ultrasound images was 96%.In conclusion,this study could help radiologists in hospitals and medical centres in classifying ultrasound images and detecting thyroid nodules.
基金support of the National Natural Science Foundation of China(No.12172023)。
文摘According to the Mindlin plate theory and the first-order piston theory,this work obtains accurate closed-form eigensolutions for the flutter problem of three-dimensional(3D)rectangular laminated panels.The governing differential equations are derived by the Hamilton's variational principle,and then solved by the iterative Separation-of-Variable(i SOV)method,which are applicable to arbitrary combinations of homogeneous Boundary Conditions(BCs).However,only the simply-support,clamped and cantilever panels are considered in this work for the sake of clarity.With the closed-form eigensolutions,the flutter frequency,flutter mode and flutter boundary are presented,and the effect of shear deformation and aerodynamic damping on flutter frequencies is investigated.Besides,the relation between panel energy and the work of aerodynamic load is discussed.The numerical comparisons reveal the following.(A)The flutter eigenvalues obtained by the present method are accurate,validated by the Finite Element Method(FEM)and the Galerkin method.(B)When the span-chord ratio is larger than 3,simplifying a 3D panel to 2D(two-dimensional)panel is reasonable and the relative differences of the flutter points predicted by the two models are less than one percent.(C)The reciprocal relationship between the mechanical energy of the panel and the work done by aerodynamic load is verified by using the present flutter eigenvalues and modes,further indicating the high accuracy of the present solutions.(D)The coupling of shear deformation and aerodynamic damping prevents frequency coalescing.
基金financially supported by the National Key Research and Development Program of China(Nos.2023YFC3904800)the National Outstanding Young Scientists Fund(No.52125002)+6 种基金the National Science Foundation of China(No.22476073 and U24A20194)the Key Project of Jiangxi Provincial Research and Development Program(Nos.20223BBG74006and 20243BBI91001)the Jiangsu Special Fund on Technology Innovation of Carbon Dioxide Peaking and Carbon Neutrality(No.BT2024011)the China Postdoctoral Science Foundation(Nos.2024M751282 and 2025T180353)the“Thousand Talents Program”of Jiangxi Province(S2021GDQN2161)the Key Project of Ganzhou City Research and Development Program(No.2023PGX17350)the Key Laboratory of Jiangxi Province for Functional Biology and Pollution Control in Red Soil Regions(No.2023SSY02051)。
文摘Recovering LiFePO_(4) extraction slag(LES)-the FePO_(4)-rich residue formed after Li leaching from spent LiFePO_(4)-has become pivotal to minimizing resource losses,mitigating environmental risks,and advancing circularity in lithium-ion battery value chains.However,integrative frameworks that link closed-loop routes(returning to battery precursors/cathodes)with non-closed-loop upcycling are still limited,constraining process optimization and scale-up.This review synthesizes current progress in LES recycling with emphasis on maximizing recovery efficiency and product value.In closed-loop pathways,hydrometallurgical purification removes impurities to yield battery-grade FePO_(4) as an LiFePO_(4) precursor,while direct relithiation(e.g.,solid-state sintering aided by Li sources and reductants)restores Li and reduces Fe^(3+)to Fe^(2+),thereby regenerating LiFePO_(4) cathodes from LES.In non-closed-loop pathways,compositionally guided upcycling converts LES into advanced materials(e.g.,high-performance electrodes,highcapacity adsorbents),thereby broadening the techno-economic value propositions.We also distill lessons from early industrial practice,identifying constraints arising from feedstock variability,energy-cost coupling(thermal/chemical utilities),and product-quality assurance(battery-grade specifications).Finally,we map research directions-including data-driven feed characterization and process control,defecthealing relithiation strategies and interfacial engineering,quality grading and market pathways,and multi-scenario deployment-to enhance the technical and economic sustainability of LES recycling and accelerate its contribution to a circular battery economy.
基金the National Natural Science Foundation of China(22479047,22409058)the Outstanding Youth Scientist Foundation of Hunan Province(2022JJ10023)the Provincial Natural Science Foundation of Guangdong(2023A1515011745)for financial support of this research。
文摘To ease the scarcity of lithium(Li)resource and cut down on environmental pollution,an efficient,selective,inexpensive and sustainable Li recycling process from waste batteries is needed,which is yet to be achieved.Here,we report a low-potential photoelectrochemical(PEC)system that selectively and efficiently extracts Li metals from multi-cation electrolytes under 1 sun illumination.Based on the difference of redox potential,we can get rid of the disturbance of other cations(i.e.,Fe,Co and Ni ions)by a bias-free PEC device to realize the extraction of high-purity Li metals on a coplanar Si-based photocathode-TiO_(2) photoanode tandem device at 2 V of applied bias(far less than the redox potentials of Li^(+)/Li).In such system,the extraction rate of Li metals(purity>99.5%)exceeds 1.35 g h^(-1)m^(-2)with 90%of Faradaic efficiency.Long-term experiments,different electrode/electrolyte tests,and various price assessments further demonstrate the stability,compatibility and economy of PEC extraction system,enabling a solar-driven pathway for the recycling of critical metal resources.
基金the Young Elite Scientists Sponsorship Program by JXAST(2024QT11)the National Natural Science Foundation of China(22465001,22309003)the Jiangxi Provincial Natural Science Foundation(20232BAB203042,20242BAB22002).
文摘As a key low-carbon energy source,nuclear power plays a vital role in the global transition toward sustainable energy.Photocatalytic uranium extraction from seawater(UES)offers a promising solution to ensure long-term uranium supply but is challenged by ultra-low uranium concentrations and ion interference.To overcome these issues,we design three diketopyrrolopyrrole-based covalent organic frameworks(COFs)via a synergisticπ-extended lock and carboxyl-functionalized anchor molecular engineering strategy.Among them,TPy-DPP-COF features a covalently lockedπ-conjugated structure that enhances planarity,optimizes energy alignment,and minimizes exciton binding energy,thereby promoting charge transfer and suppressing recombination.Concurrently,carboxyl groups enable uranyl-specific coordination and create local electric fields to facilitate charge separation.These features contribute to the outstanding performance of TPy-DPP-COF,which achieves a high uranium adsorption capacity of 16.33 mg g−1 in natural seawater under irradiation,with only 29.3%capacity loss after 10 cycles,surpassing industrial benchmarks.Density functional theory(DFT)calculations and experimental studies reveal a synergistic photocatalysis-adsorption pathway,with DPP units acting as active sites for uranium reduction.This work highlights a molecular design strategy for developing efficient COF-based photocatalysts for practical marine uranium recovery.
文摘AIM:To investigate the long-term outcomes in acute primary angle closure(APAC)patients treated with lens extraction(LE)surgery and to identify risk factors for glaucomatous optic neuropathy(GON).METHODS:In this longitudinal observational study,detailed medical histories of APAC patients and comprehensive ophthalmic examinations at final followup were collected.Logistic regression analysis was performed to identify predictors of blindness.Univariate and multivariate linear regression analyses were conducted to determine risk factors associated with visual outcomes.RESULTS:This study included 39 affected eyes of 31 subjects(26 females)with an average age of 74.1±8.0y.At 6.7±4.2y after APAC attack,2(5.7%)eyes had bestcorrected visual acuity(VA)worse than 3/60.Advanced glaucomatous visual field loss was observed in 15(39.5%)affected eyes and 5(25.0%)fellow eyes.Nine affected eyes(23.7%)had GON,and 11(28.9%)were blind.Six(15.4%)affected eyes and 2(9.1%)fellow eyes had suspicious progression.A significantly higher blindness rate in factory workers compared to office workers.Logistic regression identified that worse VA at attack(OR 10.568,95%CI 1.288-86.695;P=0.028)and worse early postoperative VA(OR 13.214,95%CI 1.157-150.881;P=0.038)were risk factors for blindness.Multivariate regression showed that longer duration of elevated intraocular pressure(P=0.004)and worse early postoperative VA(P=0.009)were associated with worse visual outcomes.CONCLUSION:Despite LE surgery,some APAC patients experience continued visual function deterioration.Lifelong monitoring is necessary.Target pressure and progression rates should be re-evaluated during follow-up.
基金supported by the Fundamental Research Funds for the Central Universities(Grant No.2025XJSB01)the Founda-tion of State Key Laboratory for Geomechanics and Deep Under-ground Engineering,China University of Mining&Technology,Beijing.(Grant No.SKLGDUEK 2217)the Collaborative Inno-vation Center for Prevention and Control of Mountain Geological Hazards of Zhejiang Province(PCMGH-2022-03).
文摘Discontinuity traces significantly impact the mechanical properties of rock masses,making their rapid and accurate identification crucial for stability analysis.We propose a framework using the multi-scale surface variation index(MsSVI)and transfer-learning enhanced artificial neural network(ANN)for efficient discontinuity trace extraction from rock mass point clouds.Leveraging the similarity between regular geometric bodies and engineering rock masses,we extract trace feature points without manual threshold selection.Our contributions include:(1)An adaptive radius MsSVI calculation method based on density information;(2)a universal trace feature point classification model trained using MsSVI and ANN via inductive transfer learning;and(3)a random sampling L1-medial skeleton algorithm for precise trace feature point extraction,bypassing point cloud triangulation.Experimental results show that our model achieves a 90.2%F1-score on test sets,demonstrating its accuracy and robustness.Furthermore,our method excels in trace detail extraction on two datasets,surpassing existing models and highlighting its potential for rock mass structural analysis.
基金funded by the U.S.National Institute for Occupational Safety and Health(NIOSH)under the Contract No.75D30119C06044。
文摘In the last two decades,significant research has been conducted in the field of automated extraction of rock mass discontinuity characteristics from three-dimensional(3D)models.This provides several methodologies for acquiring discontinuity measurements from 3D models,such as point clouds generated using laser scanning or photogrammetry.However,even with numerous automated and semiautomated methods presented in the literature,there is not one single method that can automatically characterize discontinuities accurately in a minimum of time.In this paper,we critically review all the existing methods proposed in the literature for the extraction of discontinuity characteristics such as joint sets and orientations,persistence,joint spacing,roughness and block size using point clouds,digital elevation maps,or meshes.As a result of this review,we identify the strengths and drawbacks of each method used for extracting those characteristics.We found that the approaches based on voxels and region growing are superior in extracting joint planes from 3D point clouds.Normal tensor voting with trace growth algorithm is a robust method for measuring joint trace length from 3D meshes.Spacing is estimated by calculating the perpendicular distance between joint planes.Several independent roughness indices are presented to quantify roughness from 3D surface models,but there is a need to incorporate these indices into automated methodologies.There is a lack of efficient algorithms for direct computation of block size from 3D rock mass surface models.
