Monitoring dust optical depth(DOD)from space is critical to support China’s Tianwen Mars missions.Here,we present FAMdust(Fast Adaptive Machine-learning framework for dust retrieval),a regime-aware machine-learning f...Monitoring dust optical depth(DOD)from space is critical to support China’s Tianwen Mars missions.Here,we present FAMdust(Fast Adaptive Machine-learning framework for dust retrieval),a regime-aware machine-learning framework developed to retrieve Martian DOD from satellite thermal infrared spectra.In the absence of operational Chinese thermal infrared sounders at Mars,FAMdust is applied to observations from the Emirates Mars Infrared Spectrometer(EMIRS)onboard the Hope spacecraft,which has provided global thermal infrared measurements of the Martian atmosphere since 2021.Using EMIRS radiance spectra,FAMdust produces global DOD estimates that show strong agreement with the Montabone gridded dust dataset and independent ground-based observations from the Mars Science Laboratory(MSL)Mastcam.On an independent test set,the retrieval achieves a coefficient of determination of R2=0.96,with 96.60%of retrievals falling within the expected error envelope of±(0.05+0.15×DOD).Global DOD maps derived from EMIRS successfully capture major dust structures and regional enhancements while maintaining consistency at key landing sites.Time series comparisons with Mastcam observations demonstrate strong temporal correlation(R=0.86)and low mean bias error(MBE=0.08)across Martian Years 36–37.Relative to current products,the FAMdustderived DOD exhibits improved temporal continuity and extends global dust monitoring into MY37.These results demonstrate the capability of FAMdust to provide fast,quantitative,and globally consistent DOD retrievals and highlight its adaptability to future Mars orbiters equipped with similar infrared sensing capabilities.展开更多
Faced with the surge of massive natural-language content,information retrieval systems must handle increasingly complex queries while filtering noisy information effectively.Although conventional approaches have made ...Faced with the surge of massive natural-language content,information retrieval systems must handle increasingly complex queries while filtering noisy information effectively.Although conventional approaches have made notable progress in matching efficiency and general adaptability,they still struggle to precisely model deep semantic associations between query intent and documents in real-world environments.Such limitations can lead to ranking deviations and omission of critical information.Motivated by recent advances in large language models(LLMs)and their capability to capture deep semantics,we propose DPR-FL,a Dual-Path Retrieval method that integrates fusion-based Filtering with structured LLM Feedback.It combines direct retrieval with a generation-guided retrieval process to form cooperative information flows.By fusing candidate results from multiple sources,applying a high-dimensional semantic filtering strategy,and leveraging LLM-based semantic feedback,DPR-FL refines and optimizes the selection of relevant documents,improving both coverage and relevance.Furthermore,the framework supports adaptive weighting of candidate sources and semantic signals,enhancing robustness in heterogeneous retrieval scenarios.Together,these components enable finer-grained information selection and semantic enrichment,substantially improving retrieval performance and result reliability in complex contexts.Experimental evaluations on standard web search benchmarks,including TREC-DL’19 and DL’20,as well as low-resource BEIR datasets,demonstrate that DPR-FL achieves measurable gains across key metrics such as NDCG@10 and MAP,showing improved generalization,robustness,and adaptability in zero-shot retrieval settings.展开更多
Phase retrieval is a fundamental yet challenging problem in computational imaging due to the intrinsic loss of phase information in optical measurements,leading the inverse problem highly ill-posed.Existing iterative ...Phase retrieval is a fundamental yet challenging problem in computational imaging due to the intrinsic loss of phase information in optical measurements,leading the inverse problem highly ill-posed.Existing iterative projection and model-based methods often suffer from speckle-like artifacts and limited reconstruction fidelity.Recent advances in deep learning have enabled rapid phase inference,but network-based approaches face challenges in dataset construction,generalization,and interpretability.Here,we introduce a gradient-inspired neural optimization framework that embeds a closed-form gradient from the physical forward model into the neural learning process.This hybrid design retains the interpretability and determinism of physics-based modeling while leveraging the expressive power of neural representations,enabling robust and accurate phase recovery.We demonstrate the efficacy of this approach through proof-of-principle experiments on multiplane phase retrieval and Fourier ptychographic microscopy,achieving a favorable balance between reconstruction quality and computational efficiency compared with conventional optimization and untrained network methods.Our framework establishes a unified paradigm that combines physical modeling and neural optimization,and it can be generalized to other computational imaging applications.展开更多
Accurate retrieval of atmospheric vertical profiles is critical for improving weather prediction and climate monitoring.However,the complexity of atmospheric processes in cloudy regions poses challenges compared to th...Accurate retrieval of atmospheric vertical profiles is critical for improving weather prediction and climate monitoring.However,the complexity of atmospheric processes in cloudy regions poses challenges compared to those of clear sky scenarios.This study presents a novel framework that integrates Bayesian optimization and machine learning approaches to retrieve atmospheric vertical profiles—including temperature,humidity,ozone concentration,cloud fraction,ice water content(IWC),and liquid water content(LWC)—from hyperspectral infrared observations.Specifically,a Bayesian method was used to refine ERA5 reanalysis data by minimizing brightness temperature(BT)discrepancies against FY-4B Geostationary Interferometric Infrared Sounder(GIIRS)observations,generating a high-quality profile database(~2.8 million profiles)across diverse weather systems.The optimized profiles improve radiative consistency,reducing BT biases from>40 K to<10 K in cloudy regions.To further overcome the limitations of the Bayesian method,we developed a Transformer-Resnet hybrid model(TERNet),which achieved superior performance with RMSE values of 1.61 K(temperature),5.77%(humidity),and 2.25×10–6/6.09×10–6kg kg–1(IWC/LWC)across the entire vertical levels in all-sky conditions.The TERNet outperforms both ERA5 in cloud parameter retrieval and the GIIRS L2 product in thermodynamic profiling.Independent verification with radiosonde and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations(CALIPSO)datasets confirms the framework's reliability across various meteorological regimes.This work demonstrates the capability of combining physics-informed Bayesian methods with data-driven machine learning to fully exploit hyperspectral IR data.展开更多
The arms race between avian brood parasites and their hosts provides a classic model for studying coevolution.In one of the most widespread obligate brood parasites,the Common Cuckoo(Cuculus canorus),chicks typically ...The arms race between avian brood parasites and their hosts provides a classic model for studying coevolution.In one of the most widespread obligate brood parasites,the Common Cuckoo(Cuculus canorus),chicks typically evict all host progeny(eggs and nestlings)from the nest cup,resulting in complete reproductive failure for the host.Host parents of Common Cuckoos could thus potentially benefit from retrieving evicted eggs and nestlings into the nest cup.However,whether hosts of the Common Cuckoo exhibit such retrieval behavior has been scarcely studied.In this study,we experimentally investigated the occurrence of retrieval in a nestbox-breeding population of Daurian Redstarts(Phoenicurus auroreus),a common cavity-nesting host of the Common Cuckoo.To test the redstarts'response to an egg or a nestling outside the nest cup,we experimentally placed either a conspecific egg,a model cuckoo egg,or a redstart nestling near the rim of the nest cup.We found that redstarts never showed retrieval behavior of either eggs or nestlings.All hosts ignored the experimental nestling and conspecific egg,but most ejected the model cuckoo egg from the nestbox.Our results suggest that selection for retrieval behavior in this cavity-nesting host may be weak or even negative.We discuss several ecological and evolutionary factors that may explain the absence of retrieval in this system.展开更多
To address the operational challenges associated with retrieving abandoned,lost,or otherwise discarded fishing gear(ALDFG),this study employed a mixed orthogonal experiment to systematically evaluate the effects of se...To address the operational challenges associated with retrieving abandoned,lost,or otherwise discarded fishing gear(ALDFG),this study employed a mixed orthogonal experiment to systematically evaluate the effects of seabed quality,grapnel configuration,dragging speed,and netting parameters on retrieval efficiency.The experiment was conducted in a controlled tank environment.The results showed no statistically significant difference in retrieval efficiency between the single-grapnel and double-grapnel configurations.The rocky and mixed mud-sand-rock seabeds exhibited significantly lower efficiency compared to mud,sand,and mud-sand seabeds.The small sharp grapnel achieved the highest retrieval efficiency,significantly outperforming other grapnel configurations.Within the 0.10-0.25 m/s range,dragging speed had a limited effect on retrieval efficiency.Larger netting sizes and mesh sizes were positively correlated with retrieval success rates.This study clarifies the compatibility mechanisms between seabed quality and retrieval configuration,offering a quantitative basis for optimizing grapnel-based ALDFG retrieval systems,particularly for heterogeneous seabed,and providing a technical framework for mitigating ALDFG pollution.展开更多
Purpose:Prior Information Retrieval(IR)research synthesizes progress from individual studies,yet academia-industry collaboration dynamics remain unexplored.This study investigates:(1)productivity patterns and venues,(...Purpose:Prior Information Retrieval(IR)research synthesizes progress from individual studies,yet academia-industry collaboration dynamics remain unexplored.This study investigates:(1)productivity patterns and venues,(2)citations-downloads relationships,(3)topic evolution,and(4)collaboration trends.Design/methodology/approach:We perform an analysis of 53,471 ACM IR papers(2000–2018)using bibliometrics and DistilBERT topic modeling.Findings:We find that industry-involved papers preferred WWW/CIKM venues;collaborations dominated RecSys/CSCW.We see that academia-industry collaborations achieved the highest download-to-citation conversion rates.Academia focused on algorithms;industry on applications;collaborations bridged both with rising human-centered themes.Research implications:This is a pioneering large-scale bibliometrics revealing collaboration’s impact on IR knowledge evolution and provides a methodological framework for cross-sector analysis.Practical implications:The paper identifies optimal venues(RecSys/CSCW)for partnerships and guides joint initiatives(shared datasets,grants)to bridge academia-industry divides and enhance research translation.Originality/value:This is the first large-scale bibliometric analysis of IR academia-industry collaboration.The paper finds many novel insights,including the fact that collaboration boosts citation efficiency,enables complementary specialization,and drives topic convergence.展开更多
Background:Hormonal treatment and response as a predictor of sperm retrieval prior to microdissection testicular sperm extraction(micro-TESE)are not well established in the current literature.This study aimed to inves...Background:Hormonal treatment and response as a predictor of sperm retrieval prior to microdissection testicular sperm extraction(micro-TESE)are not well established in the current literature.This study aimed to investigate the hormonal response as a predictor of sperm retrieval among men with nonobstructive azoospermia(NOA).Methods:Seventy-seven consecutive patients who had testosterone levels≤14 nmol/L were treated medically with an aromatase inhibitor or recombinant human chorionic gonadotropin(rec-hCG)prior to micro-TESE and were included.Thirty-four(44.2%)had unexplained NOA(UNEX),25(32.5%)had Klinefelter syndrome(KS),8(10.4%)had a history of cryptorchidism(UDT),4(5.2%)had microdeletion of the Azoospermia factor C(AZFc),and 6(7.8%)were treated previously with chemotherapy.Baseline and post-treatment serum hormonal levels were documented.Pre-op testosterone levels were entered into binary logistic regressions with age,Follicle-stimulating hormone(FSH),and Luteinizing hormone(LH)levels to test for significance with sperm retrieval.We then built logistic regression models to identify predictors of successful surgical sperm retrieval(SSR).Results:Forty-five patients(58%)had successful retrieval.In 32 patients(42%),no sperm was retrieved.Both the mean pre-op testosterone and the mean testosterone change between the two groups were significant(p=0.02 and p=0.011,respectively).Receiver operating characteristic(ROC)analysis demonstrated an area under the curve(AUC)of 0.785(95%CI=0.685-0.886,p<0.001).The Youden index coefficient was calculated for KS and UNEX.The cut-off point for KS was established at 0.764(sensitivity=0.875,false positive rate[FPR]=0.111),and 0.215 for UNEX(sensitivity=0.438,FPR=0.222).We also observed a correlation between age and SSR(p=0.05).In KS patients,SSR was determined by pre-op testosterone levels irrespective of age.Conclusion:Pre-operative hormonal response is a predictor for SSR in NOA patients who were treated medically.This data may help during pre-operative counselling.展开更多
Robust motion similarity retrieval from monocular 2D pose sequences is challenged by body-scale variation,viewpoint inconsistency,translation drift,and temporal misalignment.Existing contrastive skeleton learning meth...Robust motion similarity retrieval from monocular 2D pose sequences is challenged by body-scale variation,viewpoint inconsistency,translation drift,and temporal misalignment.Existing contrastive skeleton learning methods primarily address action recognition and rarely integrate explicit geometric canonicalization for retrievaloriented metric learning.This paper proposes a spatial-temporal normalized contrastive embedding framework that unifies structured nuisance suppression with scalable similarity representation learning.A four-stage normalization pipeline—torso-scale normalization,pelvis-centered alignment,posture-axis alignment,and phase-synchronized temporal resampling—removes geometric and temporal distortions prior to embedding.The normalized sequences are encoded using an acausal dilated temporal convolutional network trained with a hybrid contrastive objective combining NT-Xent and semi-hard triplet loss,enabling both global separation and fine-grained stylistic discrimination.A prototype-based representation further supports interpretable amateur-to-professional style mapping.Experiments on a golf swing benchmark achieve a Top-1 accuracy of 91.3%,outperforming BiLSTM and Dynamic Time Warping baselines.The framework establishes an invariant and interpretable paradigmfor motion similarity retrieval applicable to broader human movement analysis tasks.展开更多
Phase retrieval problems occur in a wide range of optical systems characterized by different forward path complexities.The Gerchberg–Saxton algorithm deep unrolling technique is a state-of-the-art phase retrieval met...Phase retrieval problems occur in a wide range of optical systems characterized by different forward path complexities.The Gerchberg–Saxton algorithm deep unrolling technique is a state-of-the-art phase retrieval method.Its inference speed is determined by the complexity of the forward path.We propose FourierGSNet,an efficient Gerchberg–Saxton algorithm deep unrolling method,to achieve faster phase retrieval for applications with high forward path complexities.FourierGSNet does not directly unroll Gerchberg–Saxton iterations with the forward path of the system.Instead,it extracts physics knowledge from unrolled iterations using the Fourier transform as a simplified forward path and injects the knowledge into a cascaded neural network for phase retrieval for the actual system.We evaluated FourierGSNet on three applications with three degrees of complexities:(i)coherent diffractive imaging with Fourier transform as a simple forward path,(ii)near-field X-ray imaging with Fresnel diffraction as a medium-complexity forward path,and(iii)laser beam shaping with the entire simulated optical train as a complex forward path.We compare FourierGSNet with direct unrolling,two fitting methods,and state-of-the-art data-driven methods.Experiments show that FourierGSNet is significantly faster in inference than direct unrolling on highcomplexity applications while achieving equal or higher accuracy than compared methods.展开更多
Dielectric metasurfaces and other resonant nanophotonic systems have transformed light–matter interactions by providing exact control over electromagnetic fields.Despite the fact that these systems frequently span mu...Dielectric metasurfaces and other resonant nanophotonic systems have transformed light–matter interactions by providing exact control over electromagnetic fields.Despite the fact that these systems frequently span multiple coupling regimes and may thus exhibit rich intrinsic temporal dynamics,characterizing them has primarily relied on steady-state frequency-domain analysis.To close this gap,we present a thorough time-domain mode-retrieval framework.The decoupling of resonant modes from the background continuum is made possible by systematically extracting the complex resonant poles of a nanophotonic system directly from its transient response using the vector fitting technique and the Prony method.Specifically,we investigate resonances supported by a silicon metasurface that are quasi-bound states in the continuum(quasi-BICs).This method effectively separates radiative quasi-BIC modes and identifies their fundamental properties,such as the Q-factors.In addition,our approach uncovers a clear temporal beating behavior associated with transient mode interference that is not visible in steady-state spectral measurements.Lastly,this method is expanded to the nonlinear regime to see the third-harmonic generation signal’s temporal evolution.Our results open up possibilities for ultrafast all-optical devices with customized temporal dynamics by establishing a potent semi-analytical tool for time-resolved investigations of ultrafast dynamics in resonant nanophotonic systems.展开更多
Accurate monitoring of coastal eutrophication is critical for maintaining marine ecosystem health and supporting environmental management.However,retrieving eutrophication indicators through remote sensing remains a p...Accurate monitoring of coastal eutrophication is critical for maintaining marine ecosystem health and supporting environmental management.However,retrieving eutrophication indicators through remote sensing remains a persistent challenge due to the complex nonlinear relationships between satellite signals and water chemistry.In this study,we developed a hybrid transformer-support vector regression(SVR)model to overcome these limitations.This novel architecture bridges the gap by synergizing deep spatiotemporal feature extraction with robust small-sample regression,providing a scalable framework for coastal eutrophication monitoring.Applied to Qingdao coastal waters(2000-2022)using the Moderateresolution Imaging Spectroradiometer(MODIS)data,the proposed model achieved state-of-the-art accuracy for chemical oxygen demand(COD)(R2=0.703)and soluble reactive phosphorus(SRP)(R2=0.651),surpassing classical Random Forest(RF),1D-CNN,and hybrid baselines(CNN/LSTM-SVR).While dissolved inorganic nitrogen(DIN)retrieval remains challenging(R2=0.362)due to its non-optical nature and data resolution constraints,the model exhibited notable error stability.Spatiotemporal analysis revealed that water depth,latitude,and tidal flat proximity regulate spatial heterogeneity,while land-based nutrient fluxes and sediment-water interface processes drive summer-autumn eutrophication peaks.This research offers a robust machine learning approach for long-term coastal monitoring and valuable geospatial insights for coastal environmental management.展开更多
BACKGROUND Foley catheters are occasionally used as feeding jejunostomy tubes,particularly in resource-limited settings.While enteral tube feeding offers significant benefits,it is not without its potential complicati...BACKGROUND Foley catheters are occasionally used as feeding jejunostomy tubes,particularly in resource-limited settings.While enteral tube feeding offers significant benefits,it is not without its potential complications.CASE SUMMARY We present a case of distal migration of a Foley catheter used as a feeding jejunostomy tube in a patient with complete dysphagia due to esophageal malignancy.The tube,with its balloon lodged at the ileocecal valve,was successfully retrieved via colonoscopy,avoiding surgical intervention.CONCLUSION This case underscores the importance of device selection and secure fixation in enteral feeding to prevent tube migration,and highlights colonoscopy as a safe and minimally invasive solution for this rare complication.展开更多
BACKGROUND Buried or submucosally embedded double-J(DJ)stents present a rare but technically demanding challenge in endourology,particularly in patients with malignant ureteral obstruction and prior instrumentation.We...BACKGROUND Buried or submucosally embedded double-J(DJ)stents present a rare but technically demanding challenge in endourology,particularly in patients with malignant ureteral obstruction and prior instrumentation.We describe the case of a 72-year-old woman with metastatic bladder cancer who presented with urosepsis and right hydronephrosis.During attempted bilateral stent exchange,the left ureteral orifice and distal stent curl were completely obscured by fibrotic tissue.A combined antegrade-retrograde approach was employed:A guidewire was advanced from the nephrostomy under fluoroscopy,while controlled transurethral resection of the obstructed ureteral orifice permitted exposure and retrieval of the buried stent.A new stent was subsequently placed without complications.This hybrid technique offers an effective solution in cases where traditional retrograde stent retrieval is impossible.CASE SUMMARY A 72-year-old woman presented to the emergency department with a 2-day history of fever,nausea,and worsening malaise.She described progressive left flank discomfort and suprapubic pressure.Her medical history included muscleinvasive bladder carcinoma with metastatic spread to the vertebral column,pelvic bones,and sacrum.She was receiving immunotherapy and had undergone multiple prior chemotherapy cycles.Bilateral ureteral DJ stents had been placed several months earlier due to malignant ureteral obstruction,and a left nephrostomy tube had subsequently been inserted following a prior obstructive episode.On examination,she was febrile and clinically unwell,with left costovertebral angle tenderness.Laboratory tests revealed elevated inflammatory markers and leukocytosis.Computed tomography(CT)imaging demonstrated right-sided hydronephrosis despite the presence of a DJ stent,with the left kidney adequately decompressed through the nephrostomy tube.Urine and blood cultures were obtained,and intravenous antibiotics and hydration were initiated.Despite 48 hours of conservative treatment,the patient showed no clinical improvement.Given the persistent hydronephrosis and the need for source control,the decision was made to perform bilateral stent exchange.CONCLUSION On examination,she was febrile and clinically unwell,with left costovertebral angle tenderness.Laboratory tests revealed elevated inflammatory markers and leukocytosis.CT imaging demonstrated right-sided hydronephrosis despite the presence of a DJ stent,with the left kidney adequately decompressed through the nephrostomy tube.Urine and blood cultures were obtained,and intravenous antibiotics and hydration were initiated.Despite 48 hours of conservative treatment,the patient showed no clinical improvement.Given the persistent hydronephrosis and the need for source control,the decision was made to perform bilateral stent exchange.展开更多
As a core course for information literacy education in colleges and universities,Literature Information Retrieval and Utilization directly affects the cultivation of students'academic research ability and lifelong...As a core course for information literacy education in colleges and universities,Literature Information Retrieval and Utilization directly affects the cultivation of students'academic research ability and lifelong learning ability.Its design and improvement have become important research topics in the field of higher education.Focusing on the core dimensions of curriculum design including curriculum content construction,teaching model innovation,practical link design,and assessment system optimization,we emphasize the adaptive adjustments and improvement paths of curriculum design in the digital context.Based on relevant course research results,this paper analyzes prominent problems in current curriculum design,such as the disconnection between content and scientific research practice,rigid teaching models,and single assessment methods.To address these issues,it proposes that curriculum design should adhere to three guiding principles:being demand-oriented,practice-oriented,and technology integration-oriented.This paper aims to provide theoretical reference and practical support for colleges and universities to optimize the curriculum system and improve teaching quality.展开更多
Accurate retrieval of casting 3D models is crucial for process reuse.Current methods primarily focus on shape similarity,neglecting process design features,which compromises reusability.In this study,a novel deep lear...Accurate retrieval of casting 3D models is crucial for process reuse.Current methods primarily focus on shape similarity,neglecting process design features,which compromises reusability.In this study,a novel deep learning retrieval method for process reuse was proposed,which integrates process design features into the retrieval of casting 3D models.This method leverages the comparative language-image pretraining(CLIP)model to extract shape features from the three views and sectional views of the casting model and combines them with process design features such as modulus,main wall thickness,symmetry,and length-to-height ratio to enhance process reusability.A database of 230 production casting models was established for model validation.Results indicate that incorporating process design features improves model accuracy by 6.09%,reaching 97.82%,and increases process similarity by 30.25%.The reusability of the process was further verified using the casting simulation software EasyCast.The results show that the process retrieved after integrating process design features produces the least shrinkage in the target model,demonstrating this method’s superior ability for process reuse.This approach does not require a large dataset for training and optimization,making it highly applicable to casting process design and related manufacturing processes.展开更多
Oncological microdissection testicular sperm extraction(onco-micro-TESE)represents a significant breakthrough for patients with nonobstructive azoospermia(NOA)and a concomitant in situ testicular tumor,to be managed a...Oncological microdissection testicular sperm extraction(onco-micro-TESE)represents a significant breakthrough for patients with nonobstructive azoospermia(NOA)and a concomitant in situ testicular tumor,to be managed at the time of sperm retrieval.Onco-micro-TESE addresses the dual objectives of treating both infertility and the testicular tumor simultaneously.The technique is intricate,necessitating a comprehensive understanding of testicular anatomy,physiology,tumor biology,and advanced microsurgical methods.It aims to carefully extract viable spermatozoa while minimizing the risk of tumor dissemination.This review encapsulates the procedural intricacies,evaluates success determinants,including tumor pathology and spermatogenic tissue health,and discusses the implementation of imaging techniques for enhanced surgical precision.Ethical considerations are paramount,as the procedure implicates complex decision-making that weighs the potential oncological risks against the profound desire for fatherhood using the male gametes.The review aims to provide a holistic overview of onco-micro-TESE,detailing methodological advances,clinical outcomes,and the ethical landscape,thus offering an indispensable resource for clinicians navigating this multifaceted clinical scenario.展开更多
At present,the polymerase chain reaction(PCR)amplification-based file retrieval method is the mostcommonly used and effective means of DNA file retrieval.The number of orthogonal primers limitsthe number of files that...At present,the polymerase chain reaction(PCR)amplification-based file retrieval method is the mostcommonly used and effective means of DNA file retrieval.The number of orthogonal primers limitsthe number of files that can be accurately accessed,which in turn affects the density in a single oligo poolof digital DNA storage.In this paper,a multi-mode DNA sequence design method based on PCR file retrie-val in a single oligonucleotide pool is proposed for high-capacity DNA data storage.Firstly,by analyzingthe maximum number of orthogonal primers at each predicted primer length,it was found that the rela-tionship between primer length and the maximum available primer number does not increase linearly,and the maximum number of orthogonal primers is on the order of 104.Next,this paper analyzes themaximum address space capacity of DNA sequences with different types of primer binding sites for filemapping.In the case where the capacity of the primer library is R(where R is even),the number ofaddress spaces that can be mapped by the single-primer DNA sequence design scheme proposed in thispaper is four times that of the previous one,and the two-level primer DNA sequence design scheme can reach [R/2·(R/2-1)]2times.Finally,a multi-mode DNA sequence generation method is designed based onthe number of files to be stored in the oligonucleotide pool,in order to meet the requirements of the ran-dom retrieval of target files in an oligonucleotide pool with large-scale file numbers.The performance ofthe primers generated by the orthogonal primer library generator proposed in this paper is verified,andthe average Gibbs free energy of the most stable heterodimer formed between the orthogonal primersproduced is−1 kcal·(mol·L−1)−1(1 kcal=4.184 kJ).At the same time,by selectively PCR-amplifying theDNA sequences of the two-level primer binding sites for random access,the target sequence can be accu-rately read with a minimum of 103 reads,when the primer binding site sequences at different positionsare mutually different.This paper provides a pipeline for orthogonal primer library generation and multi-mode mapping schemes between files and primers,which can help achieve precise random access to filesin large-scale DNA oligo pools.展开更多
This study describes the use of the weighted multiplicative algebraic reconstruction technique(WMART)to obtain vertical ozone profiles from limb observations performed by the scanning imaging absorption spectrometer f...This study describes the use of the weighted multiplicative algebraic reconstruction technique(WMART)to obtain vertical ozone profiles from limb observations performed by the scanning imaging absorption spectrometer for atmospheric chartography(SCIAMACHY).This technique is based on SaskMART(the combination of the multiplicative algebraic reconstruction technique and SaskTRAN radiative transfer model),which was originally developed for optical spectrometer and infrared imaging system(OSIRIS)data.One of the objectives of this study was to obtain consistent ozone profiles from the two satellites.In this study,the WMART algorithm is combined with a radiative transfer model(SCIATRAN),as well as a set of measurement vectors comprising five Hartley pairing vectors(HPVs)and one Chappuis triplet vector(CTV),to retrieve ozone profiles in the altitude range of 10–69 km.Considering that the weighting factors in WMART have a significant effect on the retrievals,we propose a novel approach to calculate the pairriplet weighting factors using wavelength weighting functions.The results of the application of the proposed ozone retrieval scheme are compared with the SCIAMACHY v3.5 ozone product by University of Bremen and validated against profiles derived from other passive satellite observations or measured by ozonesondes.Between 18 and 55 km,the retrieved ozone profiles typically agree with data from the SCIAMACHY ozone product within 5%for tropics and middle latitudes,whereas a negative deviation exists between 35 and 50 km for northern high latitudes,with a deviation of less than 10%above 50 km.Comparison of the retrieved profiles with microwave limb sounder(MLS)v5.0 indicates that the difference is within±5%between 18 and 55 km,and an agreement within 10%is achieved in other altitudes for tropics and middle latitudes.Comparison of the retrieved profiles with OSIRIS v7.1 indicates that the average deviation is within±5%between 20 and 59 km,and difference of approximately 10%is achieved below 20 km.Compared with ozonesondes data,a general validity of the retrievals is no more than 5%between 15 and 30 km.展开更多
Aerosol optical depth(AOD)and fine particulate matter with a diameter of less than or equal to 2.5μm(PM2.5)play crucial roles in air quality,human health,and climate change.However,the complex correlation of AOD–...Aerosol optical depth(AOD)and fine particulate matter with a diameter of less than or equal to 2.5μm(PM2.5)play crucial roles in air quality,human health,and climate change.However,the complex correlation of AOD–PM2.5and the limitations of existing algorithms pose a significant challenge in realizing the accurate joint retrieval of these two parameters at the same location.On this point,a multi-task learning(MTL)model,which enables the joint retrieval of PM2.5concentration and AOD,is proposed and applied on the top-of-the-atmosphere reflectance data gathered by the Fengyun-4A Advanced Geosynchronous Radiation Imager(FY-4A AGRI),and compared to that of two single-task learning models—namely,Random Forest(RF)and Deep Neural Network(DNN).Specifically,MTL achieves a coefficient of determination(R2)of 0.88 and a root-mean-square error(RMSE)of 0.10 in AOD retrieval.In comparison to RF,the R2increases by 0.04,the RMSE decreases by 0.02,and the percentage of retrieval results falling within the expected error range(Within-EE)rises by 5.55%.The R2and RMSE of PM2.5retrieval by MTL are 0.84 and 13.76μg m~(-3)respectively.Compared with RF,the R2increases by 0.06,the RMSE decreases by 4.55μg m~(-3),and the Within-EE increases by 7.28%.Additionally,compared to DNN,MTL shows an increase of 0.01 in R2and a decrease of 0.02 in RMSE in AOD retrieval,with a corresponding increase of 2.89%in Within-EE.For PM2.5retrieval,MTL exhibits an increase of 0.05 in R2,a decrease of 1.76μg m~(-3)in RMSE,and an increase of 6.83%in Within-EE.The evaluation suggests that MTL is able to provide simultaneously improved AOD and PM2.5retrievals,demonstrating a significant advantage in efficiently capturing the spatial distribution of PM2.5concentration and AOD.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.42575151)the National Key Research and Development Program of China(Grant No.2023YFF0714804)the State Key Laboratory of Atmospheric Environment and Extreme Meteorology(Grant Nos.2024QN11 and 2024QN04).
摘要Monitoring dust optical depth(DOD)from space is critical to support China’s Tianwen Mars missions.Here,we present FAMdust(Fast Adaptive Machine-learning framework for dust retrieval),a regime-aware machine-learning framework developed to retrieve Martian DOD from satellite thermal infrared spectra.In the absence of operational Chinese thermal infrared sounders at Mars,FAMdust is applied to observations from the Emirates Mars Infrared Spectrometer(EMIRS)onboard the Hope spacecraft,which has provided global thermal infrared measurements of the Martian atmosphere since 2021.Using EMIRS radiance spectra,FAMdust produces global DOD estimates that show strong agreement with the Montabone gridded dust dataset and independent ground-based observations from the Mars Science Laboratory(MSL)Mastcam.On an independent test set,the retrieval achieves a coefficient of determination of R2=0.96,with 96.60%of retrievals falling within the expected error envelope of±(0.05+0.15×DOD).Global DOD maps derived from EMIRS successfully capture major dust structures and regional enhancements while maintaining consistency at key landing sites.Time series comparisons with Mastcam observations demonstrate strong temporal correlation(R=0.86)and low mean bias error(MBE=0.08)across Martian Years 36–37.Relative to current products,the FAMdustderived DOD exhibits improved temporal continuity and extends global dust monitoring into MY37.These results demonstrate the capability of FAMdust to provide fast,quantitative,and globally consistent DOD retrievals and highlight its adaptability to future Mars orbiters equipped with similar infrared sensing capabilities.
基金funded by the National Natural Science Foundation of China(42371466)the Key Research and Development Program of Henan Province(251111211700)+2 种基金the Key Research Projects of Henan Higher Education Institutions(23A520031,24A520020,25B520012)the Henan Provincial Archives Bureau Scientific and Technological Project(2025-Z-002)and the Science and Technology Plan Project of Housing and Urban-Rural Development in Henan Province(HNJS-2024-K35).
摘要Faced with the surge of massive natural-language content,information retrieval systems must handle increasingly complex queries while filtering noisy information effectively.Although conventional approaches have made notable progress in matching efficiency and general adaptability,they still struggle to precisely model deep semantic associations between query intent and documents in real-world environments.Such limitations can lead to ranking deviations and omission of critical information.Motivated by recent advances in large language models(LLMs)and their capability to capture deep semantics,we propose DPR-FL,a Dual-Path Retrieval method that integrates fusion-based Filtering with structured LLM Feedback.It combines direct retrieval with a generation-guided retrieval process to form cooperative information flows.By fusing candidate results from multiple sources,applying a high-dimensional semantic filtering strategy,and leveraging LLM-based semantic feedback,DPR-FL refines and optimizes the selection of relevant documents,improving both coverage and relevance.Furthermore,the framework supports adaptive weighting of candidate sources and semantic signals,enhancing robustness in heterogeneous retrieval scenarios.Together,these components enable finer-grained information selection and semantic enrichment,substantially improving retrieval performance and result reliability in complex contexts.Experimental evaluations on standard web search benchmarks,including TREC-DL’19 and DL’20,as well as low-resource BEIR datasets,demonstrate that DPR-FL achieves measurable gains across key metrics such as NDCG@10 and MAP,showing improved generalization,robustness,and adaptability in zero-shot retrieval settings.
基金supported by the National Natural Science Foundation of China(Grant No.62275178)。
摘要Phase retrieval is a fundamental yet challenging problem in computational imaging due to the intrinsic loss of phase information in optical measurements,leading the inverse problem highly ill-posed.Existing iterative projection and model-based methods often suffer from speckle-like artifacts and limited reconstruction fidelity.Recent advances in deep learning have enabled rapid phase inference,but network-based approaches face challenges in dataset construction,generalization,and interpretability.Here,we introduce a gradient-inspired neural optimization framework that embeds a closed-form gradient from the physical forward model into the neural learning process.This hybrid design retains the interpretability and determinism of physics-based modeling while leveraging the expressive power of neural representations,enabling robust and accurate phase recovery.We demonstrate the efficacy of this approach through proof-of-principle experiments on multiplane phase retrieval and Fourier ptychographic microscopy,achieving a favorable balance between reconstruction quality and computational efficiency compared with conventional optimization and untrained network methods.Our framework establishes a unified paradigm that combines physical modeling and neural optimization,and it can be generalized to other computational imaging applications.
基金supported by the National Natural Science Foundation of China under Grant U2442219Fengyun Satellite Application Pioneer Program(2023)Special Initiative on Numerical Weather Prediction(NWP)Applications,the Civil Aerospace Technology Pre-Research Project(D040405)the Joint Funds of the Zhejiang Provincial Natural Science Foundation of China under Grant No.LZJMZ23D050003。
摘要Accurate retrieval of atmospheric vertical profiles is critical for improving weather prediction and climate monitoring.However,the complexity of atmospheric processes in cloudy regions poses challenges compared to those of clear sky scenarios.This study presents a novel framework that integrates Bayesian optimization and machine learning approaches to retrieve atmospheric vertical profiles—including temperature,humidity,ozone concentration,cloud fraction,ice water content(IWC),and liquid water content(LWC)—from hyperspectral infrared observations.Specifically,a Bayesian method was used to refine ERA5 reanalysis data by minimizing brightness temperature(BT)discrepancies against FY-4B Geostationary Interferometric Infrared Sounder(GIIRS)observations,generating a high-quality profile database(~2.8 million profiles)across diverse weather systems.The optimized profiles improve radiative consistency,reducing BT biases from>40 K to<10 K in cloudy regions.To further overcome the limitations of the Bayesian method,we developed a Transformer-Resnet hybrid model(TERNet),which achieved superior performance with RMSE values of 1.61 K(temperature),5.77%(humidity),and 2.25×10–6/6.09×10–6kg kg–1(IWC/LWC)across the entire vertical levels in all-sky conditions.The TERNet outperforms both ERA5 in cloud parameter retrieval and the GIIRS L2 product in thermodynamic profiling.Independent verification with radiosonde and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations(CALIPSO)datasets confirms the framework's reliability across various meteorological regimes.This work demonstrates the capability of combining physics-informed Bayesian methods with data-driven machine learning to fully exploit hyperspectral IR data.
基金supported by the startup fund from Beijing Normal University(312200502560 to J.Z.)the National Natural Science Foundation of China(32501383 to J.Z.,and 31672297 and 32271559 to W.D.)the Max Planck Society(to B.K.)。
摘要The arms race between avian brood parasites and their hosts provides a classic model for studying coevolution.In one of the most widespread obligate brood parasites,the Common Cuckoo(Cuculus canorus),chicks typically evict all host progeny(eggs and nestlings)from the nest cup,resulting in complete reproductive failure for the host.Host parents of Common Cuckoos could thus potentially benefit from retrieving evicted eggs and nestlings into the nest cup.However,whether hosts of the Common Cuckoo exhibit such retrieval behavior has been scarcely studied.In this study,we experimentally investigated the occurrence of retrieval in a nestbox-breeding population of Daurian Redstarts(Phoenicurus auroreus),a common cavity-nesting host of the Common Cuckoo.To test the redstarts'response to an egg or a nestling outside the nest cup,we experimentally placed either a conspecific egg,a model cuckoo egg,or a redstart nestling near the rim of the nest cup.We found that redstarts never showed retrieval behavior of either eggs or nestlings.All hosts ignored the experimental nestling and conspecific egg,but most ejected the model cuckoo egg from the nestbox.Our results suggest that selection for retrieval behavior in this cavity-nesting host may be weak or even negative.We discuss several ecological and evolutionary factors that may explain the absence of retrieval in this system.
基金funded by the National Key R&D Program of China(No.2023YFD2401301)the World Wide Fund for Nature(No.Ocean-A000072).
摘要To address the operational challenges associated with retrieving abandoned,lost,or otherwise discarded fishing gear(ALDFG),this study employed a mixed orthogonal experiment to systematically evaluate the effects of seabed quality,grapnel configuration,dragging speed,and netting parameters on retrieval efficiency.The experiment was conducted in a controlled tank environment.The results showed no statistically significant difference in retrieval efficiency between the single-grapnel and double-grapnel configurations.The rocky and mixed mud-sand-rock seabeds exhibited significantly lower efficiency compared to mud,sand,and mud-sand seabeds.The small sharp grapnel achieved the highest retrieval efficiency,significantly outperforming other grapnel configurations.Within the 0.10-0.25 m/s range,dragging speed had a limited effect on retrieval efficiency.Larger netting sizes and mesh sizes were positively correlated with retrieval success rates.This study clarifies the compatibility mechanisms between seabed quality and retrieval configuration,offering a quantitative basis for optimizing grapnel-based ALDFG retrieval systems,particularly for heterogeneous seabed,and providing a technical framework for mitigating ALDFG pollution.
基金Yi Bu's participation in this work was in part supported by the National Science Foundation of China(#24&ZD072).
摘要Purpose:Prior Information Retrieval(IR)research synthesizes progress from individual studies,yet academia-industry collaboration dynamics remain unexplored.This study investigates:(1)productivity patterns and venues,(2)citations-downloads relationships,(3)topic evolution,and(4)collaboration trends.Design/methodology/approach:We perform an analysis of 53,471 ACM IR papers(2000–2018)using bibliometrics and DistilBERT topic modeling.Findings:We find that industry-involved papers preferred WWW/CIKM venues;collaborations dominated RecSys/CSCW.We see that academia-industry collaborations achieved the highest download-to-citation conversion rates.Academia focused on algorithms;industry on applications;collaborations bridged both with rising human-centered themes.Research implications:This is a pioneering large-scale bibliometrics revealing collaboration’s impact on IR knowledge evolution and provides a methodological framework for cross-sector analysis.Practical implications:The paper identifies optimal venues(RecSys/CSCW)for partnerships and guides joint initiatives(shared datasets,grants)to bridge academia-industry divides and enhance research translation.Originality/value:This is the first large-scale bibliometric analysis of IR academia-industry collaboration.The paper finds many novel insights,including the fact that collaboration boosts citation efficiency,enables complementary specialization,and drives topic convergence.
摘要Background:Hormonal treatment and response as a predictor of sperm retrieval prior to microdissection testicular sperm extraction(micro-TESE)are not well established in the current literature.This study aimed to investigate the hormonal response as a predictor of sperm retrieval among men with nonobstructive azoospermia(NOA).Methods:Seventy-seven consecutive patients who had testosterone levels≤14 nmol/L were treated medically with an aromatase inhibitor or recombinant human chorionic gonadotropin(rec-hCG)prior to micro-TESE and were included.Thirty-four(44.2%)had unexplained NOA(UNEX),25(32.5%)had Klinefelter syndrome(KS),8(10.4%)had a history of cryptorchidism(UDT),4(5.2%)had microdeletion of the Azoospermia factor C(AZFc),and 6(7.8%)were treated previously with chemotherapy.Baseline and post-treatment serum hormonal levels were documented.Pre-op testosterone levels were entered into binary logistic regressions with age,Follicle-stimulating hormone(FSH),and Luteinizing hormone(LH)levels to test for significance with sperm retrieval.We then built logistic regression models to identify predictors of successful surgical sperm retrieval(SSR).Results:Forty-five patients(58%)had successful retrieval.In 32 patients(42%),no sperm was retrieved.Both the mean pre-op testosterone and the mean testosterone change between the two groups were significant(p=0.02 and p=0.011,respectively).Receiver operating characteristic(ROC)analysis demonstrated an area under the curve(AUC)of 0.785(95%CI=0.685-0.886,p<0.001).The Youden index coefficient was calculated for KS and UNEX.The cut-off point for KS was established at 0.764(sensitivity=0.875,false positive rate[FPR]=0.111),and 0.215 for UNEX(sensitivity=0.438,FPR=0.222).We also observed a correlation between age and SSR(p=0.05).In KS patients,SSR was determined by pre-op testosterone levels irrespective of age.Conclusion:Pre-operative hormonal response is a predictor for SSR in NOA patients who were treated medically.This data may help during pre-operative counselling.
基金supported by Incheon National University Research Grant(2020).
摘要Robust motion similarity retrieval from monocular 2D pose sequences is challenged by body-scale variation,viewpoint inconsistency,translation drift,and temporal misalignment.Existing contrastive skeleton learning methods primarily address action recognition and rarely integrate explicit geometric canonicalization for retrievaloriented metric learning.This paper proposes a spatial-temporal normalized contrastive embedding framework that unifies structured nuisance suppression with scalable similarity representation learning.A four-stage normalization pipeline—torso-scale normalization,pelvis-centered alignment,posture-axis alignment,and phase-synchronized temporal resampling—removes geometric and temporal distortions prior to embedding.The normalized sequences are encoded using an acausal dilated temporal convolutional network trained with a hybrid contrastive objective combining NT-Xent and semi-hard triplet loss,enabling both global separation and fine-grained stylistic discrimination.A prototype-based representation further supports interpretable amateur-to-professional style mapping.Experiments on a golf swing benchmark achieve a Top-1 accuracy of 91.3%,outperforming BiLSTM and Dynamic Time Warping baselines.The framework establishes an invariant and interpretable paradigmfor motion similarity retrieval applicable to broader human movement analysis tasks.
基金supported by the EU In Sha Pe Project funded by the European Union(Grant No.101058523)the AIMS5.0 Project funded by the EU Chips Joint Undertaking(Chips JU)the Dutch National Funding Agency(RVO)(Grant No.101112089)。
摘要Phase retrieval problems occur in a wide range of optical systems characterized by different forward path complexities.The Gerchberg–Saxton algorithm deep unrolling technique is a state-of-the-art phase retrieval method.Its inference speed is determined by the complexity of the forward path.We propose FourierGSNet,an efficient Gerchberg–Saxton algorithm deep unrolling method,to achieve faster phase retrieval for applications with high forward path complexities.FourierGSNet does not directly unroll Gerchberg–Saxton iterations with the forward path of the system.Instead,it extracts physics knowledge from unrolled iterations using the Fourier transform as a simplified forward path and injects the knowledge into a cascaded neural network for phase retrieval for the actual system.We evaluated FourierGSNet on three applications with three degrees of complexities:(i)coherent diffractive imaging with Fourier transform as a simple forward path,(ii)near-field X-ray imaging with Fresnel diffraction as a medium-complexity forward path,and(iii)laser beam shaping with the entire simulated optical train as a complex forward path.We compare FourierGSNet with direct unrolling,two fitting methods,and state-of-the-art data-driven methods.Experiments show that FourierGSNet is significantly faster in inference than direct unrolling on highcomplexity applications while achieving equal or higher accuracy than compared methods.
摘要Dielectric metasurfaces and other resonant nanophotonic systems have transformed light–matter interactions by providing exact control over electromagnetic fields.Despite the fact that these systems frequently span multiple coupling regimes and may thus exhibit rich intrinsic temporal dynamics,characterizing them has primarily relied on steady-state frequency-domain analysis.To close this gap,we present a thorough time-domain mode-retrieval framework.The decoupling of resonant modes from the background continuum is made possible by systematically extracting the complex resonant poles of a nanophotonic system directly from its transient response using the vector fitting technique and the Prony method.Specifically,we investigate resonances supported by a silicon metasurface that are quasi-bound states in the continuum(quasi-BICs).This method effectively separates radiative quasi-BIC modes and identifies their fundamental properties,such as the Q-factors.In addition,our approach uncovers a clear temporal beating behavior associated with transient mode interference that is not visible in steady-state spectral measurements.Lastly,this method is expanded to the nonlinear regime to see the third-harmonic generation signal’s temporal evolution.Our results open up possibilities for ultrafast all-optical devices with customized temporal dynamics by establishing a potent semi-analytical tool for time-resolved investigations of ultrafast dynamics in resonant nanophotonic systems.
基金Supported by the National Natural Science Foundation of China(No.42476246)the Natural Science Foundation of Shandong Province(No.ZR2020QD065)。
摘要Accurate monitoring of coastal eutrophication is critical for maintaining marine ecosystem health and supporting environmental management.However,retrieving eutrophication indicators through remote sensing remains a persistent challenge due to the complex nonlinear relationships between satellite signals and water chemistry.In this study,we developed a hybrid transformer-support vector regression(SVR)model to overcome these limitations.This novel architecture bridges the gap by synergizing deep spatiotemporal feature extraction with robust small-sample regression,providing a scalable framework for coastal eutrophication monitoring.Applied to Qingdao coastal waters(2000-2022)using the Moderateresolution Imaging Spectroradiometer(MODIS)data,the proposed model achieved state-of-the-art accuracy for chemical oxygen demand(COD)(R2=0.703)and soluble reactive phosphorus(SRP)(R2=0.651),surpassing classical Random Forest(RF),1D-CNN,and hybrid baselines(CNN/LSTM-SVR).While dissolved inorganic nitrogen(DIN)retrieval remains challenging(R2=0.362)due to its non-optical nature and data resolution constraints,the model exhibited notable error stability.Spatiotemporal analysis revealed that water depth,latitude,and tidal flat proximity regulate spatial heterogeneity,while land-based nutrient fluxes and sediment-water interface processes drive summer-autumn eutrophication peaks.This research offers a robust machine learning approach for long-term coastal monitoring and valuable geospatial insights for coastal environmental management.
摘要BACKGROUND Foley catheters are occasionally used as feeding jejunostomy tubes,particularly in resource-limited settings.While enteral tube feeding offers significant benefits,it is not without its potential complications.CASE SUMMARY We present a case of distal migration of a Foley catheter used as a feeding jejunostomy tube in a patient with complete dysphagia due to esophageal malignancy.The tube,with its balloon lodged at the ileocecal valve,was successfully retrieved via colonoscopy,avoiding surgical intervention.CONCLUSION This case underscores the importance of device selection and secure fixation in enteral feeding to prevent tube migration,and highlights colonoscopy as a safe and minimally invasive solution for this rare complication.
摘要BACKGROUND Buried or submucosally embedded double-J(DJ)stents present a rare but technically demanding challenge in endourology,particularly in patients with malignant ureteral obstruction and prior instrumentation.We describe the case of a 72-year-old woman with metastatic bladder cancer who presented with urosepsis and right hydronephrosis.During attempted bilateral stent exchange,the left ureteral orifice and distal stent curl were completely obscured by fibrotic tissue.A combined antegrade-retrograde approach was employed:A guidewire was advanced from the nephrostomy under fluoroscopy,while controlled transurethral resection of the obstructed ureteral orifice permitted exposure and retrieval of the buried stent.A new stent was subsequently placed without complications.This hybrid technique offers an effective solution in cases where traditional retrograde stent retrieval is impossible.CASE SUMMARY A 72-year-old woman presented to the emergency department with a 2-day history of fever,nausea,and worsening malaise.She described progressive left flank discomfort and suprapubic pressure.Her medical history included muscleinvasive bladder carcinoma with metastatic spread to the vertebral column,pelvic bones,and sacrum.She was receiving immunotherapy and had undergone multiple prior chemotherapy cycles.Bilateral ureteral DJ stents had been placed several months earlier due to malignant ureteral obstruction,and a left nephrostomy tube had subsequently been inserted following a prior obstructive episode.On examination,she was febrile and clinically unwell,with left costovertebral angle tenderness.Laboratory tests revealed elevated inflammatory markers and leukocytosis.Computed tomography(CT)imaging demonstrated right-sided hydronephrosis despite the presence of a DJ stent,with the left kidney adequately decompressed through the nephrostomy tube.Urine and blood cultures were obtained,and intravenous antibiotics and hydration were initiated.Despite 48 hours of conservative treatment,the patient showed no clinical improvement.Given the persistent hydronephrosis and the need for source control,the decision was made to perform bilateral stent exchange.CONCLUSION On examination,she was febrile and clinically unwell,with left costovertebral angle tenderness.Laboratory tests revealed elevated inflammatory markers and leukocytosis.CT imaging demonstrated right-sided hydronephrosis despite the presence of a DJ stent,with the left kidney adequately decompressed through the nephrostomy tube.Urine and blood cultures were obtained,and intravenous antibiotics and hydration were initiated.Despite 48 hours of conservative treatment,the patient showed no clinical improvement.Given the persistent hydronephrosis and the need for source control,the decision was made to perform bilateral stent exchange.
摘要As a core course for information literacy education in colleges and universities,Literature Information Retrieval and Utilization directly affects the cultivation of students'academic research ability and lifelong learning ability.Its design and improvement have become important research topics in the field of higher education.Focusing on the core dimensions of curriculum design including curriculum content construction,teaching model innovation,practical link design,and assessment system optimization,we emphasize the adaptive adjustments and improvement paths of curriculum design in the digital context.Based on relevant course research results,this paper analyzes prominent problems in current curriculum design,such as the disconnection between content and scientific research practice,rigid teaching models,and single assessment methods.To address these issues,it proposes that curriculum design should adhere to three guiding principles:being demand-oriented,practice-oriented,and technology integration-oriented.This paper aims to provide theoretical reference and practical support for colleges and universities to optimize the curriculum system and improve teaching quality.
基金supported by the National Natural Science Foundation of China(Nos.52074246,52275390,52375394)the National Defense Basic Scientific Research Program of China(No.JCKY2020408B002)the Key R&D Program of Shanxi Province(No.202102050201011).
摘要Accurate retrieval of casting 3D models is crucial for process reuse.Current methods primarily focus on shape similarity,neglecting process design features,which compromises reusability.In this study,a novel deep learning retrieval method for process reuse was proposed,which integrates process design features into the retrieval of casting 3D models.This method leverages the comparative language-image pretraining(CLIP)model to extract shape features from the three views and sectional views of the casting model and combines them with process design features such as modulus,main wall thickness,symmetry,and length-to-height ratio to enhance process reusability.A database of 230 production casting models was established for model validation.Results indicate that incorporating process design features improves model accuracy by 6.09%,reaching 97.82%,and increases process similarity by 30.25%.The reusability of the process was further verified using the casting simulation software EasyCast.The results show that the process retrieved after integrating process design features produces the least shrinkage in the target model,demonstrating this method’s superior ability for process reuse.This approach does not require a large dataset for training and optimization,making it highly applicable to casting process design and related manufacturing processes.
基金supported by the National Natural Science Foundation of China(No.82371633)Peking University Clinical Scientist Training Program and the Fundamental Research Funds for the Central University(BMU2023PYJ H012).
摘要Oncological microdissection testicular sperm extraction(onco-micro-TESE)represents a significant breakthrough for patients with nonobstructive azoospermia(NOA)and a concomitant in situ testicular tumor,to be managed at the time of sperm retrieval.Onco-micro-TESE addresses the dual objectives of treating both infertility and the testicular tumor simultaneously.The technique is intricate,necessitating a comprehensive understanding of testicular anatomy,physiology,tumor biology,and advanced microsurgical methods.It aims to carefully extract viable spermatozoa while minimizing the risk of tumor dissemination.This review encapsulates the procedural intricacies,evaluates success determinants,including tumor pathology and spermatogenic tissue health,and discusses the implementation of imaging techniques for enhanced surgical precision.Ethical considerations are paramount,as the procedure implicates complex decision-making that weighs the potential oncological risks against the profound desire for fatherhood using the male gametes.The review aims to provide a holistic overview of onco-micro-TESE,detailing methodological advances,clinical outcomes,and the ethical landscape,thus offering an indispensable resource for clinicians navigating this multifaceted clinical scenario.
基金supported by the fund from Tianjin Municipal Science and Technology Bureau(22JCYBJC01390).
摘要At present,the polymerase chain reaction(PCR)amplification-based file retrieval method is the mostcommonly used and effective means of DNA file retrieval.The number of orthogonal primers limitsthe number of files that can be accurately accessed,which in turn affects the density in a single oligo poolof digital DNA storage.In this paper,a multi-mode DNA sequence design method based on PCR file retrie-val in a single oligonucleotide pool is proposed for high-capacity DNA data storage.Firstly,by analyzingthe maximum number of orthogonal primers at each predicted primer length,it was found that the rela-tionship between primer length and the maximum available primer number does not increase linearly,and the maximum number of orthogonal primers is on the order of 104.Next,this paper analyzes themaximum address space capacity of DNA sequences with different types of primer binding sites for filemapping.In the case where the capacity of the primer library is R(where R is even),the number ofaddress spaces that can be mapped by the single-primer DNA sequence design scheme proposed in thispaper is four times that of the previous one,and the two-level primer DNA sequence design scheme can reach [R/2·(R/2-1)]2times.Finally,a multi-mode DNA sequence generation method is designed based onthe number of files to be stored in the oligonucleotide pool,in order to meet the requirements of the ran-dom retrieval of target files in an oligonucleotide pool with large-scale file numbers.The performance ofthe primers generated by the orthogonal primer library generator proposed in this paper is verified,andthe average Gibbs free energy of the most stable heterodimer formed between the orthogonal primersproduced is−1 kcal·(mol·L−1)−1(1 kcal=4.184 kJ).At the same time,by selectively PCR-amplifying theDNA sequences of the two-level primer binding sites for random access,the target sequence can be accu-rately read with a minimum of 103 reads,when the primer binding site sequences at different positionsare mutually different.This paper provides a pipeline for orthogonal primer library generation and multi-mode mapping schemes between files and primers,which can help achieve precise random access to filesin large-scale DNA oligo pools.
基金supported by the National Science Foundations of China(No.61905256)the National Key Research and Development Program of China(No.2019YFC0214702)the Youth Innovation Promotion Association of Chinese Academy of Sciences(No.2020439)。
摘要This study describes the use of the weighted multiplicative algebraic reconstruction technique(WMART)to obtain vertical ozone profiles from limb observations performed by the scanning imaging absorption spectrometer for atmospheric chartography(SCIAMACHY).This technique is based on SaskMART(the combination of the multiplicative algebraic reconstruction technique and SaskTRAN radiative transfer model),which was originally developed for optical spectrometer and infrared imaging system(OSIRIS)data.One of the objectives of this study was to obtain consistent ozone profiles from the two satellites.In this study,the WMART algorithm is combined with a radiative transfer model(SCIATRAN),as well as a set of measurement vectors comprising five Hartley pairing vectors(HPVs)and one Chappuis triplet vector(CTV),to retrieve ozone profiles in the altitude range of 10–69 km.Considering that the weighting factors in WMART have a significant effect on the retrievals,we propose a novel approach to calculate the pairriplet weighting factors using wavelength weighting functions.The results of the application of the proposed ozone retrieval scheme are compared with the SCIAMACHY v3.5 ozone product by University of Bremen and validated against profiles derived from other passive satellite observations or measured by ozonesondes.Between 18 and 55 km,the retrieved ozone profiles typically agree with data from the SCIAMACHY ozone product within 5%for tropics and middle latitudes,whereas a negative deviation exists between 35 and 50 km for northern high latitudes,with a deviation of less than 10%above 50 km.Comparison of the retrieved profiles with microwave limb sounder(MLS)v5.0 indicates that the difference is within±5%between 18 and 55 km,and an agreement within 10%is achieved in other altitudes for tropics and middle latitudes.Comparison of the retrieved profiles with OSIRIS v7.1 indicates that the average deviation is within±5%between 20 and 59 km,and difference of approximately 10%is achieved below 20 km.Compared with ozonesondes data,a general validity of the retrievals is no more than 5%between 15 and 30 km.
基金supported by the National Natural Science Foundation of China(Grant Nos.42030708,42375138,42030608,42105128,42075079)the Opening Foundation of Key Laboratory of Atmospheric Sounding,China Meteorological Administration(CMA),and the CMA Research Center on Meteorological Observation Engineering Technology(Grant No.U2021Z03),and the Opening Foundation of the Key Laboratory of Atmospheric Chemistry,CMA(Grant No.2022B02)。
摘要Aerosol optical depth(AOD)and fine particulate matter with a diameter of less than or equal to 2.5μm(PM2.5)play crucial roles in air quality,human health,and climate change.However,the complex correlation of AOD–PM2.5and the limitations of existing algorithms pose a significant challenge in realizing the accurate joint retrieval of these two parameters at the same location.On this point,a multi-task learning(MTL)model,which enables the joint retrieval of PM2.5concentration and AOD,is proposed and applied on the top-of-the-atmosphere reflectance data gathered by the Fengyun-4A Advanced Geosynchronous Radiation Imager(FY-4A AGRI),and compared to that of two single-task learning models—namely,Random Forest(RF)and Deep Neural Network(DNN).Specifically,MTL achieves a coefficient of determination(R2)of 0.88 and a root-mean-square error(RMSE)of 0.10 in AOD retrieval.In comparison to RF,the R2increases by 0.04,the RMSE decreases by 0.02,and the percentage of retrieval results falling within the expected error range(Within-EE)rises by 5.55%.The R2and RMSE of PM2.5retrieval by MTL are 0.84 and 13.76μg m~(-3)respectively.Compared with RF,the R2increases by 0.06,the RMSE decreases by 4.55μg m~(-3),and the Within-EE increases by 7.28%.Additionally,compared to DNN,MTL shows an increase of 0.01 in R2and a decrease of 0.02 in RMSE in AOD retrieval,with a corresponding increase of 2.89%in Within-EE.For PM2.5retrieval,MTL exhibits an increase of 0.05 in R2,a decrease of 1.76μg m~(-3)in RMSE,and an increase of 6.83%in Within-EE.The evaluation suggests that MTL is able to provide simultaneously improved AOD and PM2.5retrievals,demonstrating a significant advantage in efficiently capturing the spatial distribution of PM2.5concentration and AOD.