BACKGROUND Hepatocellular carcinoma(HCC)in segments VII and VIII poses technical challenges for both liver resection and radiofrequency ablation(RFA).Robotic-assisted techniques may enhance safety and precision,but co...BACKGROUND Hepatocellular carcinoma(HCC)in segments VII and VIII poses technical challenges for both liver resection and radiofrequency ablation(RFA).Robotic-assisted techniques may enhance safety and precision,but comparative evidence remains limited.AIM To compare the clinical outcomes of robotic liver resection(R-LR)and robotic intraoperative RFA(RIO-RFA)for HCC located in liver segments VII and VIII.METHODS We retrospectively analyzed 93 HCC patients in segments VII/VIII with de novo(n=57)or first recurrent(n=36).HCC who underwent R-LR or RIO-RFA between 2015 and 2024.Propensity score matching was performed to reduce selection bias.Primary outcomes were overall survival(OS)and recurrence-free survival(RFS).Kaplan-Meier curves,log-rank tests,and Cox regression were used to identify prognostic factors for OS and RFS.RESULTS In the de novo group,OS and RFS did not differ significantly between R-LR and RIO-RFA before or after propensity score matching.In contrast,the recurrent group showed significantly improved OS and RFS with R-LR(P=0.005 and P=0.012,respectively).Subgroup analyses revealed that low-risk de novo patients with smaller tumors achieved superior OS after R-LR,whereas carefully selected low-risk recurrent patients undergoing RIO-RFA(smaller tumors,absence of complications)achieved outcomes comparable to R-LR.Platelet count,tumor size,and postoperative complications constituted key prognostic factors.CONCLUSION For HCC in challenging liver segments VII and VIII,R-LR and RIO-RFA achieve comparable outcomes in de novo cases,whereas R-LR confers superior survival in recurrent disease.R-LR should be prioritized for small de novo HCCs and for recurrent disease overall;RIO-RFA may serve as an effective alternative in carefully selected lowrisk recurrent patients.Tumor size,platelet count,and postoperative complications are key prognostic indicators to guide individualized treatment.展开更多
To enhance the properties of bio-based polyesters,enabling them to more closely mimic the characteristics of terephthalate-based materials,a series of aliphatic-aromatic copolyesters(P_(1)–P_(4))were synthesized via ...To enhance the properties of bio-based polyesters,enabling them to more closely mimic the characteristics of terephthalate-based materials,a series of aliphatic-aromatic copolyesters(P_(1)–P_(4))were synthesized via melt polycondensation.Diester monomers M and N were synthesized via the Williamson reaction,using lignin-derived 2-methoxyhydroquinone,methyl 4-chloromethylbenzoate,and methyl chloroacetate as starting materials.Hydroquinone bis(2-hydroxyethyl)ether(HQEE)and 1,4-cyclohexanedimethanol(CHDM)were employed as cyclic segments,while 1,4-butanediol(BDO)and 1,6-hexanediol(HDO)served as alkyl segments within the copolymer structures.The novel copolyesters exhibited molecular weights(Mw)in the range of 5.25×10^(4)–5.87×10^(4) g/mol,with polydispersity indices spanning from 2.50–2.66.Evaluation of the structural and thermomechanical properties indicated that the inclusion of alkyl segments induced a reduction in both crystallinity and molecular weight,while significantly improving the flexibility,whereas cyclic segments enhanced the processability of the copolyesters.Copolyesters P_(1) and P_(2),due to the presence of rigid segments(HQEE and CHDM),displayed relatively high glass transition temperatures(Tg>80℃)and melting temperatures(Tm>170℃).Notably,P_(2),incorporating CHDM,exhibited superior elongation properties(272%),attributed to the enhanced chain mobility resulting from its trans-conformation,while P_(1) was found to be likely brittle owing to excessive chain stiffness.Biodegradability assessment using earthworms as bioindicators revealed that the copolyesters demonstrated moderate degradation profiles,with P_(2) exhibiting a degradation rate of 4.82%,followed by P_(4) at 4.07%,P_(3) at 3.65%,and P_(1) at 3.17%.The higher degradation rate of P_(2) was attributed to its relatively larger d-spacing and lower toxicity,which facilitated enzymatic hydrolytic attack by microorganisms.These findings highlight the significance of optimizing the structural chain segments within aliphatic-aromatic copolyesters.By doing so,it is possible to significantly enhance their properties and performance,offering viable bio-based alternatives to petroleum-based polyesters such as polyethylene terephthalate(PET).展开更多
Water hammer diagnostics is an important fracturing diagnosis technique to evaluate fracture locations and other downhole events in fracturing. The evaluation results are obtained by analyzing shut-in water hammer pre...Water hammer diagnostics is an important fracturing diagnosis technique to evaluate fracture locations and other downhole events in fracturing. The evaluation results are obtained by analyzing shut-in water hammer pressure signal. The field-sampled water hammer signal is often disturbed by noise interference. Noise interference exists in various pumping stages during water hammer diagnostics, with significantly different frequency range and energy distribution. Clarifying the differences in frequency range and energy distribution between effective water hammer signals and noise is the basis of setting specific filtering parameters, including filtering frequency range and energy thresholds. Filtering specifically could separate the effective signal and noise, which is the key to ensuring the accuracy of water hammer diagnosis. As an emerging technique, there is a lack of research on the frequency range and energy distribution of effective signals in water hammer diagnostics. In this paper, the frequency range and energy distribution characteristics of field-sampled water hammer signals were clarified quantitatively and qualitatively for the first time by a newly proposed comprehensive water hammer segmentation-energy analysis method. The water hammer signals were preprocessed and divided into three segments, including pre-shut-in, water hammer oscillation, and leak-off segment. Then, the three segments were analyzed by energy analysis and correlation analysis. The results indicated that, one aspect, the frequency range of water hammer oscillation spans from 0 to 0.65 Hz, considered as effective water hammer signal. The pre-shut-in and leak-off segment ranges from 0 to 0.35 Hz and 0-0.2 Hz respectively. Meanwhile, odd harmonics were manifested in water hammer oscillation segment, with the harmonic frequencies ranging approximately from 0.07 to 0.75 Hz. Whereas integer harmonics were observed in pre-shut-in segment, ranging from 6 to 40 Hz. The other aspect, the energy distribution of water hammer signals was analyzed in different frequency ranges. In 0-1 Hz, an exponential decay was observed in all three segments. In 1-100 Hz, a periodical energy distribution was observed in pre-shut-in segment, an exponential decay was observed in water hammer oscillation, and an even energy distribution was observed in leak-off segment. In 100-500 Hz, an even energy distribution was observed in those three segments, yet the highest magnitude was noted in leak-off segment. In this study, the effective frequency range and energy distribution characteristics of the field-sampled water hammer signals in different segments were sufficiently elucidated quantitatively and qualitatively for the first time, laying the groundwork for optimizing the filtering parameters of the field filtering models and advancing the accuracy of identifying downhole event locations.展开更多
AIM: To investigate the efficacy of Ferrara rings (FR) implantation in the treatment of keratoconus.METHODS: It was a retrospective case series descriptive study. The sample was comprised of 50 patients 79 eyes diagno...AIM: To investigate the efficacy of Ferrara rings (FR) implantation in the treatment of keratoconus.METHODS: It was a retrospective case series descriptive study. The sample was comprised of 50 patients 79 eyes diagnosed with progressive keratoconus. This included 24 (48%) males and 26 (52%) females between the age of 13 and 44 years. All participants underwent surgical implantation of FR in the period between January 2009 and September 2010 at Jordan University Hospital. Thorough ophthalmologic examinations were applied to measure vital variables for each pathological condition before and after surgery. RESULTS: Findings indicated an overall significant postoperative improvement in both uncorrected visual acuity (UCVA) and best spectacle corrected visual acuity (BSCVA) throughout follow up visits. Moreover, results illustrated a significant decrease in spherical equivalent (SE) and keratometric readings (lower, higher and the average). CONCLUSION: Surgical intervention strategies are being frequently developed to meet the needs of patients with keratoconus. The implantation of Ferrara rings has proven to be a safe and feasible alternative procedure for the treatment of mild-moderate keratoconus especially for patients with contact lenses intolerance. We have found that this procedure has improved visual outcomes in all eyes studied. Nevertheless, further research is needed to investigate long term outcomes.展开更多
[Objective] The aim was to study the conditions of tissue culture regeneration seedling by using the stem segments of Euphorbia tirucalli and determine the optimum culture condition of each culture stage,so as to prov...[Objective] The aim was to study the conditions of tissue culture regeneration seedling by using the stem segments of Euphorbia tirucalli and determine the optimum culture condition of each culture stage,so as to provide references for the factory production and relative study of tissue culture seedling of E. tirucalli. [Method] Taking the stem segments of E. tirucalli as explants,the effects of various mediums on germination rate,multiplication coefficient and rooting rate were studied. [Result] The optimum induction medium of germination culture was 1/2MS＋NAA 0.02 mg/L＋6-BA 1.0 mg/L,with differentiation rate of 89.7%; the best subculture medium was 1/2MS＋NAA 0.02 mg/L＋6-BA 0.60 mg/L＋AD 3.0 mg/L,with multiplication coefficient of 5.70; the optimum rooting culture medium was 1/2MS＋NAA 0.40 mg/L＋IBA 0.4 mg/L,with rooting rate of 100% and transplanting survival rate of 80%. [Conclusion] The tissue culture conditions of stem segments of E. tirucalli were determined primarily.展开更多
Advanced traffic monitoring systems encounter substantial challenges in vehicle detection and classification due to the limitations of conventional methods,which often demand extensive computational resources and stru...Advanced traffic monitoring systems encounter substantial challenges in vehicle detection and classification due to the limitations of conventional methods,which often demand extensive computational resources and struggle with diverse data acquisition techniques.This research presents a novel approach for vehicle classification and recognition in aerial image sequences,integrating multiple advanced techniques to enhance detection accuracy.The proposed model begins with preprocessing using Multiscale Retinex(MSR)to enhance image quality,followed by Expectation-Maximization(EM)Segmentation for precise foreground object identification.Vehicle detection is performed using the state-of-the-art YOLOv10 framework,while feature extraction incorporates Maximally Stable Extremal Regions(MSER),Dense Scale-Invariant Feature Transform(Dense SIFT),and Zernike Moments Features to capture distinct object characteristics.Feature optimization is further refined through a Hybrid Swarm-based Optimization algorithm,ensuring optimal feature selection for improved classification performance.The final classification is conducted using a Vision Transformer,leveraging its robust learning capabilities for enhanced accuracy.Experimental evaluations on benchmark datasets,including UAVDT and the Unmanned Aerial Vehicle Intruder Dataset(UAVID),demonstrate the superiority of the proposed approach,achieving an accuracy of 94.40%on UAVDT and 93.57%on UAVID.The results highlight the efficacy of the model in significantly enhancing vehicle detection and classification in aerial imagery,outperforming existing methodologies and offering a statistically validated improvement for intelligent traffic monitoring systems compared to existing approaches.展开更多
Brain tumors require precise segmentation for diagnosis and treatment plans due to their complex morphology and heterogeneous characteristics.While MRI-based automatic brain tumor segmentation technology reduces the b...Brain tumors require precise segmentation for diagnosis and treatment plans due to their complex morphology and heterogeneous characteristics.While MRI-based automatic brain tumor segmentation technology reduces the burden on medical staff and provides quantitative information,existing methodologies and recent models still struggle to accurately capture and classify the fine boundaries and diverse morphologies of tumors.In order to address these challenges and maximize the performance of brain tumor segmentation,this research introduces a novel SwinUNETR-based model by integrating a new decoder block,the Hierarchical Channel-wise Attention Decoder(HCAD),into a powerful SwinUNETR encoder.The HCAD decoder block utilizes hierarchical features and channelspecific attention mechanisms to further fuse information at different scales transmitted from the encoder and preserve spatial details throughout the reconstruction phase.Rigorous evaluations on the recent BraTS GLI datasets demonstrate that the proposed SwinHCAD model achieved superior and improved segmentation accuracy on both the Dice score and HD95 metrics across all tumor subregions(WT,TC,and ET)compared to baseline models.In particular,the rationale and contribution of the model design were clarified through ablation studies to verify the effectiveness of the proposed HCAD decoder block.The results of this study are expected to greatly contribute to enhancing the efficiency of clinical diagnosis and treatment planning by increasing the precision of automated brain tumor segmentation.展开更多
High-resolution remote sensing images(HRSIs)are now an essential data source for gathering surface information due to advancements in remote sensing data capture technologies.However,their significant scale changes an...High-resolution remote sensing images(HRSIs)are now an essential data source for gathering surface information due to advancements in remote sensing data capture technologies.However,their significant scale changes and wealth of spatial details pose challenges for semantic segmentation.While convolutional neural networks(CNNs)excel at capturing local features,they are limited in modeling long-range dependencies.Conversely,transformers utilize multihead self-attention to integrate global context effectively,but this approach often incurs a high computational cost.This paper proposes a global-local multiscale context network(GLMCNet)to extract both global and local multiscale contextual information from HRSIs.A detail-enhanced filtering module(DEFM)is proposed at the end of the encoder to refine the encoder outputs further,thereby enhancing the key details extracted by the encoder and effectively suppressing redundant information.In addition,a global-local multiscale transformer block(GLMTB)is proposed in the decoding stage to enable the modeling of rich multiscale global and local information.We also design a stair fusion mechanism to transmit deep semantic information from deep to shallow layers progressively.Finally,we propose the semantic awareness enhancement module(SAEM),which further enhances the representation of multiscale semantic features through spatial attention and covariance channel attention.Extensive ablation analyses and comparative experiments were conducted to evaluate the performance of the proposed method.Specifically,our method achieved a mean Intersection over Union(mIoU)of 86.89%on the ISPRS Potsdam dataset and 84.34%on the ISPRS Vaihingen dataset,outperforming existing models such as ABCNet and BANet.展开更多
This systematic review aims to comprehensively examine and compare deep learning methods for brain tumor segmentation and classification using MRI and other imaging modalities,focusing on recent trends from 2022 to 20...This systematic review aims to comprehensively examine and compare deep learning methods for brain tumor segmentation and classification using MRI and other imaging modalities,focusing on recent trends from 2022 to 2025.The primary objective is to evaluate methodological advancements,model performance,dataset usage,and existing challenges in developing clinically robust AI systems.We included peer-reviewed journal articles and highimpact conference papers published between 2022 and 2025,written in English,that proposed or evaluated deep learning methods for brain tumor segmentation and/or classification.Excluded were non-open-access publications,books,and non-English articles.A structured search was conducted across Scopus,Google Scholar,Wiley,and Taylor&Francis,with the last search performed in August 2025.Risk of bias was not formally quantified but considered during full-text screening based on dataset diversity,validation methods,and availability of performance metrics.We used narrative synthesis and tabular benchmarking to compare performance metrics(e.g.,accuracy,Dice score)across model types(CNN,Transformer,Hybrid),imaging modalities,and datasets.A total of 49 studies were included(43 journal articles and 6 conference papers).These studies spanned over 9 public datasets(e.g.,BraTS,Figshare,REMBRANDT,MOLAB)and utilized a range of imaging modalities,predominantly MRI.Hybrid models,especially ResViT and UNetFormer,consistently achieved high performance,with classification accuracy exceeding 98%and segmentation Dice scores above 0.90 across multiple studies.Transformers and hybrid architectures showed increasing adoption post2023.Many studies lacked external validation and were evaluated only on a few benchmark datasets,raising concerns about generalizability and dataset bias.Few studies addressed clinical interpretability or uncertainty quantification.Despite promising results,particularly for hybrid deep learning models,widespread clinical adoption remains limited due to lack of validation,interpretability concerns,and real-world deployment barriers.展开更多
Deep learning-based methods have become alternatives to traditional numerical weather prediction systems,offering faster computation and the ability to utilize large historical datasets.However,the application of deep...Deep learning-based methods have become alternatives to traditional numerical weather prediction systems,offering faster computation and the ability to utilize large historical datasets.However,the application of deep learning to medium-range regional weather forecasting with limited data remains a significant challenge.In this work,three key solutions are proposed:(1)motivated by the need to improve model performance in data-scarce regional forecasting scenarios,the authors innovatively apply semantic segmentation models,to better capture spatiotemporal features and improve prediction accuracy;(2)recognizing the challenge of overfitting and the inability of traditional noise-based data augmentation methods to effectively enhance model robustness,a novel learnable Gaussian noise mechanism is introduced that allows the model to adaptively optimize perturbations for different locations,ensuring more effective learning;and(3)to address the issue of error accumulation in autoregressive prediction,as well as the challenge of learning difficulty and the lack of intermediate data utilization in one-shot prediction,the authors propose a cascade prediction approach that effectively resolves these problems while significantly improving model forecasting performance.The method achieves a competitive result in The East China Regional AI Medium Range Weather Forecasting Competition.Ablation experiments further validate the effectiveness of each component,highlighting their contributions to enhancing prediction performance.展开更多
Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0.Manual inspection of products on assembly lines remains inefficient,prone t...Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0.Manual inspection of products on assembly lines remains inefficient,prone to errors and lacks consistency,emphasizing the need for a reliable and automated inspection system.Leveraging both object detection and image segmentation approaches,this research proposes a vision-based solution for the detection of various kinds of tools in the toolkit using deep learning(DL)models.Two Intel RealSense D455f depth cameras were arranged in a top down configuration to capture both RGB and depth images of the toolkits.After applying multiple constraints and enhancing them through preprocessing and augmentation,a dataset consisting of 3300 annotated RGB-D photos was generated.Several DL models were selected through a comprehensive assessment of mean Average Precision(mAP),precision-recall equilibrium,inference latency(target≥30 FPS),and computational burden,resulting in a preference for YOLO and Region-based Convolutional Neural Networks(R-CNN)variants over ViT-based models due to the latter’s increased latency and resource requirements.YOLOV5,YOLOV8,YOLOV11,Faster R-CNN,and Mask R-CNN were trained on the annotated dataset and evaluated using key performance metrics(Recall,Accuracy,F1-score,and Precision).YOLOV11 demonstrated balanced excellence with 93.0%precision,89.9%recall,and a 90.6%F1-score in object detection,as well as 96.9%precision,95.3%recall,and a 96.5%F1-score in instance segmentation with an average inference time of 25 ms per frame(≈40 FPS),demonstrating real-time performance.Leveraging these results,a YOLOV11-based windows application was successfully deployed in a real-time assembly line environment,where it accurately processed live video streams to detect and segment tools within toolkits,demonstrating its practical effectiveness in industrial automation.The application is capable of precisely measuring socket dimensions by utilising edge detection techniques on YOLOv11 segmentation masks,in addition to detection and segmentation.This makes it possible to do specification-level quality control right on the assembly line,which improves the ability to examine things in real time.The implementation is a big step forward for intelligent manufacturing in the Industry 4.0 paradigm.It provides a scalable,efficient,and accurate way to do automated inspection and dimensional verification activities.展开更多
Bus and any other public transit connectivity issues facilitate an understanding of the importance of transit planning in enhancing existing or new transit services.Improving transit connectivity is one of the most vi...Bus and any other public transit connectivity issues facilitate an understanding of the importance of transit planning in enhancing existing or new transit services.Improving transit connectivity is one of the most vital tasks in transit-operations planning.A poor connection can cause some passengers to stop using the transit service.Service-design criteria always contain postulates to improve routing and scheduling coordination(intra-and inter-agency transfer centers/points and synchronized/timed transfers).Ostensibly the lack of well-defined connectivity measures precludes the weighing and quantifying of the result of any coordination effort.This work provides an initial methodological framework and concepts for(1)quantifying transit connectivity measures and(2)directions and tools for detecting weak segments in inter-route and inter-modal chains(paths)for possible revisions/changes.展开更多
BACKGROUND Radical resection is an important treatment method for hepatic echinococcosis.The posterosuperior segments of the liver remain the most challenging region for laparoscopic or robotic hepatectomy.AIM To demo...BACKGROUND Radical resection is an important treatment method for hepatic echinococcosis.The posterosuperior segments of the liver remain the most challenging region for laparoscopic or robotic hepatectomy.AIM To demonstrate the safety and preliminary experience of robotic radical resection of cystic and alveolar echinococcosis in posterosuperior liver segments.METHODS A retrospective analysis was conducted on the clinical data of 5 patients with a median age of 37 years(21-56 years)with cystic and alveolar echinococcosis in difficult liver lesions admitted to two centers from September to December 2019.The surgical methods included total pericystectomy,segmental hepatectomy,or hemihepatectomy.RESULTS Among the 5 patients,4 presented with cystic echinococcosis and 1 presented with alveolar echinococcosis,all of whom underwent robotic radical operation successfully without conversion to laparotomy.Total caudate lobectomy was performed in 2 cases,hepatectomy of segment Ⅶ in 1 case,total pericystectomy of segment Ⅷ in 1 case,and right hemihepatectomy in 1 case.Operation time was 225 min(175-300 min);blood loss was 100 mL(50-600 mL);and postoperative hospital stay duration was 10 d(5-19 d).The Clavien-Dindo complication grade was Ⅰ in 4 cases and Ⅱ in 1 case.No recurrence of echinococcosis was found in any patient at the 3 mo of follow-up.CONCLUSION Robotic radical surgery for cystic and selected alveolar echinococcosis in posterosuperior liver segments is safe and feasible.展开更多
Chromosome segment substitution lines（CSSLs） are useful for the precise mapping of quantitative trait loci（QTLs） and dissection of the genetic basis of complex traits.In this study,two whole-genome sequenced rice ...Chromosome segment substitution lines（CSSLs） are useful for the precise mapping of quantitative trait loci（QTLs） and dissection of the genetic basis of complex traits.In this study,two whole-genome sequenced rice cultivars,the japonica Nipponbare and indica 9311 were used as recipient and donor,respectively.A population with 57 CSSLs was developed after crossing and back-crossing assisted by molecular markers, and genotypes were identified using a high-throughput resequencing strategy.Detailed graphical genotypes of 38 lines were constructed based on resequencing data.These CSSLs had a total of 95 substituted segments derived from indica 9311,with an average of about 2.5 segments per CSSL and eight segments per chromosome,and covered about 87.4%of the rice whole genome.A multiple linear regression QTL analysis mapped four QTLs for 1000-grain weight.The largest-effect QTL was located in a region on chromosome 5 that contained a cloned major QTL GW5/qSW5 for grain size in rice.These CSSLs with a background of Nipponbare may provide powerful tools for future whole-genome展开更多
Tmnsmembrane（TM） protein plays an important role in the life activity of the cells, and the prediction of transmembrane helical segments （TMHs） is an important subject in the bioinformatics research. Thus far, sev...Tmnsmembrane（TM） protein plays an important role in the life activity of the cells, and the prediction of transmembrane helical segments （TMHs） is an important subject in the bioinformatics research. Thus far, several prediction methods have been reported, but there are some deficiencies in prediction accuracy and adaptability in these methods. In this paper, a method based on discrete wavelet transform （DWT） was developed to predict the TMHs. Two sets of test data sets containing total 60 protein sequences were utilized to access the effect of the method. Compared with the prediction results of TMHMM2.0 and MEMSAT, the obtained results indicate that the presented method has high prediction accuracy.展开更多
Since the great 1303 Hongtong, Shanxi, earthquake of magnitude 8, 700 years have elapsed. To analyze the long-term seismic potential, this paper divides the Taiyuan-Linfen portion of the Shanxi graben system into 5 se...Since the great 1303 Hongtong, Shanxi, earthquake of magnitude 8, 700 years have elapsed. To analyze the long-term seismic potential, this paper divides the Taiyuan-Linfen portion of the Shanxi graben system into 5 seismogenic segments. Based on data of historical earthquakes and GPS observation, the authors estimate mean seismic-moment rates and average recurrence intervals of strong earthquakes for the individual segments, and fur-ther analyze relative levels of current stress cumulation on the segments based on mapping b-values along the gra-ben system by using the network seismic data for the recent over 30 years. The main result shows that the Linfen basin segment has an estimated mean seismic-moment rate of 2.211016 Nm/a to 3.031016 Nm/a, and its average recurrence interval for M=7.5 earthquake is estimated to be between 1 560 and 2 140 years. For the Ling-shi-Hongtong segment, the estimated average recurrence interval for M=8 earthquakes is between 4 300 and 5 100 years, equivalent to having a mean moment-rate of 2.581016 Nm/a to 3.101016 Nm/a. The contour map of b-values shows that the two segments of Lingshi-Hongtong and Linfen basin have been being at low or relatively low stress levels, reflecting that since the 1303 M=8 and the 1695 M=7.5 earthquake ruptures, the fault-planes strengths of the both segments have not been resumed yet. And the other two segments, the Houma and the Jiexiu-Fenyang, have relatively high stress levels, and have been already identified as potential risky segments for the coming earthquakes from the analysis combining with the estimated average recurrence intervals of earth-quakes on the both segments.展开更多
Deformation and dislocations of segments of shield tunnel in construction stage have apparent effect on tunnel structure stress and even cause local cracks and breakage in tunnel. 3D finite element method was used to ...Deformation and dislocations of segments of shield tunnel in construction stage have apparent effect on tunnel structure stress and even cause local cracks and breakage in tunnel. 3D finite element method was used to analyze two segment ring models under uniform injected pressure: (1) segment ring without wedge-shaped segment, which has 16 types of preinstall erection tolerance; (2) segment ring with wedge-shaped segment, which has no preinstall erection tolerance. The analysis results indicate that different erection tolerances can cause irregular deformation in segment ring under uniform injected pressure, and that the tolerance values are enlarged further. Wedge-shaped segment apparently affects the overall deformation of segment ring without erection tolerances. The uniform injected pressure can cause deformation of ring with wedge-shaped segment irregular, and dislocations also appear in this situation. The stress of segment with erection tolerances is much larger than that of segment without erection tolerances. Enlarging the central angle of wedge-shaped segment can make the irregular deformation and dis- locations of segments smaller. The analysis results also provide basis for erection tolerance control and improvement of segment constitution.展开更多
In this study, we examined the thermal effects throughout the process of the placement of span-scale girder segments on a 6×110-m continuous steel box girder in the Hong Kong-Zhuhai-Macao Bridge. Firstly, when a ...In this study, we examined the thermal effects throughout the process of the placement of span-scale girder segments on a 6×110-m continuous steel box girder in the Hong Kong-Zhuhai-Macao Bridge. Firstly, when a span-scale girder segment is temporarily stored in the open air, temperature gradients will significantly increase the maximum reaction force on temporary supports and cause local buckling at the bottom of the girder segment. Secondly, due to the temperature difference of the girder segments before and after girth-welding, some residual thermal deflections will appear on the girder segments because the boundary conditions of the structure are changed by the girth-welding. Thirdly, the thermal expansion and thermal bending of girder segments will cause movement and rotation of bearings, which must be considered in setting bearings. We propose control measures for these problems based on finite element method simulation with field-measured temperatures. The local buckling during open-air storage can be avoided by reasonably determining the appropriate positions of temporary supports using analysis of overall and local stresses. The residual thermal deflections can be overcome by performing girth-welding during a period when the vertical temperature difference of the girder is within 1 °C, such as after 22:00. Some formulas are proposed to determine the pre-set distances for bearings, in which the movement and rotation of the bearings due to dead loads and thermal loads are considered. Finally, the feasibility of these control measures in the placement of span-scale girder segments on a real continuous girder was verified: no local buckling was observed during open-air storage;the residual thermal deflections after girth-welding were controlled within 5 mm and the residual pre-set distances of bearings when the whole continuous girder reached its design state were controlled within 20 mm.展开更多
BACKGROUND：Previous tissue-engineered nerve studies have focused on artificial nerve and nerve cell cultures.The effects of regeneration chambers with autologous nerve bridging for the repair of nerve defects remain ...BACKGROUND：Previous tissue-engineered nerve studies have focused on artificial nerve and nerve cell cultures.The effects of regeneration chambers with autologous nerve bridging for the repair of nerve defects remain unclear.OBJECTIVE：To explore the feasibility and advantages of chitosan tube bridging autologous nerve segments for repairing 12-mm sciatic nerve defects in rats.DESIGN,TIME AND SETTING：A randomized,controlled,animal study using nerve tissue engineering was performed at the Animal Laboratory and Laboratory of Histology and Embryology,Liaoning Medical University from June 2008 to March 2009.MATERIALS：Chitosan powder was purchased from Jinan Haidebei Marine Bioengineering,China.METHODS：A sciatic nerve segment of approximately 8 mm was excised from the posterior margin of the piriformis muscle of Sprague Dawley rats.The two nerve ends shrank to form a 12-mm defect,and the nerve defect was repaired using a chitosan tube bridging autologous nerve segment （bridge group）,a chitosan tube-encapsulated autologous nerve segment （encapsulation group）,and a chitosan tube alone （chitosan tube alone group）,respectively.MAIN OUTCOME MEASURES：Histological and ultrastructural changes of the injured sciatic nerve;number of regenerated myelinated nerve fibers; nerve conduction velocity; leg muscle atrophy; and sciatic nerve functional index.RESULTS：At 4 months after implantation,the chitosan tube was absorbed.The tube was thin,but maintained the original shape,and vascular proliferation was observed around the tube.In the bridge group,regenerative myelinated nerve fibers were thick and orderly,with a thick myelin sheath and intact axonal structure.The number of myelinated nerve fibers and nerve conduction velocity were significantly greater compared with the other groups （P〈 0.01）.Moreover,nerve and muscle function was significantly improved following chitosan tube bridging autologous nerve segment treatment compared with the other groups （P〈 0.05 or P 〈 0.01）.CONCLUSION：Chitosan tube bridging autologous nerve segments exhibited better repair effects on nerve defects compared with chitosan tubeencapsulated autologous nerve segments and a chitosan tube alone.This method provided a simple and effective treatment for long-segmental nerve defects.展开更多
基金Supported by Feng Chia University/Chung Shan Medical University,No.FCU/CSMU 112-001Taiwan National Science and Technology Council,No.NSTC 114-2221-E-035-036.
文摘BACKGROUND Hepatocellular carcinoma(HCC)in segments VII and VIII poses technical challenges for both liver resection and radiofrequency ablation(RFA).Robotic-assisted techniques may enhance safety and precision,but comparative evidence remains limited.AIM To compare the clinical outcomes of robotic liver resection(R-LR)and robotic intraoperative RFA(RIO-RFA)for HCC located in liver segments VII and VIII.METHODS We retrospectively analyzed 93 HCC patients in segments VII/VIII with de novo(n=57)or first recurrent(n=36).HCC who underwent R-LR or RIO-RFA between 2015 and 2024.Propensity score matching was performed to reduce selection bias.Primary outcomes were overall survival(OS)and recurrence-free survival(RFS).Kaplan-Meier curves,log-rank tests,and Cox regression were used to identify prognostic factors for OS and RFS.RESULTS In the de novo group,OS and RFS did not differ significantly between R-LR and RIO-RFA before or after propensity score matching.In contrast,the recurrent group showed significantly improved OS and RFS with R-LR(P=0.005 and P=0.012,respectively).Subgroup analyses revealed that low-risk de novo patients with smaller tumors achieved superior OS after R-LR,whereas carefully selected low-risk recurrent patients undergoing RIO-RFA(smaller tumors,absence of complications)achieved outcomes comparable to R-LR.Platelet count,tumor size,and postoperative complications constituted key prognostic factors.CONCLUSION For HCC in challenging liver segments VII and VIII,R-LR and RIO-RFA achieve comparable outcomes in de novo cases,whereas R-LR confers superior survival in recurrent disease.R-LR should be prioritized for small de novo HCCs and for recurrent disease overall;RIO-RFA may serve as an effective alternative in carefully selected lowrisk recurrent patients.Tumor size,platelet count,and postoperative complications are key prognostic indicators to guide individualized treatment.
基金financially supported by State Administration of Foreign Experts Affairs(SAFEA)through the High-End Foreign Expert Program(No.BG2021227001)postdoctoral funding from Wuhan University of Science and Technology(No.105008701)。
文摘To enhance the properties of bio-based polyesters,enabling them to more closely mimic the characteristics of terephthalate-based materials,a series of aliphatic-aromatic copolyesters(P_(1)–P_(4))were synthesized via melt polycondensation.Diester monomers M and N were synthesized via the Williamson reaction,using lignin-derived 2-methoxyhydroquinone,methyl 4-chloromethylbenzoate,and methyl chloroacetate as starting materials.Hydroquinone bis(2-hydroxyethyl)ether(HQEE)and 1,4-cyclohexanedimethanol(CHDM)were employed as cyclic segments,while 1,4-butanediol(BDO)and 1,6-hexanediol(HDO)served as alkyl segments within the copolymer structures.The novel copolyesters exhibited molecular weights(Mw)in the range of 5.25×10^(4)–5.87×10^(4) g/mol,with polydispersity indices spanning from 2.50–2.66.Evaluation of the structural and thermomechanical properties indicated that the inclusion of alkyl segments induced a reduction in both crystallinity and molecular weight,while significantly improving the flexibility,whereas cyclic segments enhanced the processability of the copolyesters.Copolyesters P_(1) and P_(2),due to the presence of rigid segments(HQEE and CHDM),displayed relatively high glass transition temperatures(Tg>80℃)and melting temperatures(Tm>170℃).Notably,P_(2),incorporating CHDM,exhibited superior elongation properties(272%),attributed to the enhanced chain mobility resulting from its trans-conformation,while P_(1) was found to be likely brittle owing to excessive chain stiffness.Biodegradability assessment using earthworms as bioindicators revealed that the copolyesters demonstrated moderate degradation profiles,with P_(2) exhibiting a degradation rate of 4.82%,followed by P_(4) at 4.07%,P_(3) at 3.65%,and P_(1) at 3.17%.The higher degradation rate of P_(2) was attributed to its relatively larger d-spacing and lower toxicity,which facilitated enzymatic hydrolytic attack by microorganisms.These findings highlight the significance of optimizing the structural chain segments within aliphatic-aromatic copolyesters.By doing so,it is possible to significantly enhance their properties and performance,offering viable bio-based alternatives to petroleum-based polyesters such as polyethylene terephthalate(PET).
基金support from the National Natural Science Foundation of China(No.52374019).
文摘Water hammer diagnostics is an important fracturing diagnosis technique to evaluate fracture locations and other downhole events in fracturing. The evaluation results are obtained by analyzing shut-in water hammer pressure signal. The field-sampled water hammer signal is often disturbed by noise interference. Noise interference exists in various pumping stages during water hammer diagnostics, with significantly different frequency range and energy distribution. Clarifying the differences in frequency range and energy distribution between effective water hammer signals and noise is the basis of setting specific filtering parameters, including filtering frequency range and energy thresholds. Filtering specifically could separate the effective signal and noise, which is the key to ensuring the accuracy of water hammer diagnosis. As an emerging technique, there is a lack of research on the frequency range and energy distribution of effective signals in water hammer diagnostics. In this paper, the frequency range and energy distribution characteristics of field-sampled water hammer signals were clarified quantitatively and qualitatively for the first time by a newly proposed comprehensive water hammer segmentation-energy analysis method. The water hammer signals were preprocessed and divided into three segments, including pre-shut-in, water hammer oscillation, and leak-off segment. Then, the three segments were analyzed by energy analysis and correlation analysis. The results indicated that, one aspect, the frequency range of water hammer oscillation spans from 0 to 0.65 Hz, considered as effective water hammer signal. The pre-shut-in and leak-off segment ranges from 0 to 0.35 Hz and 0-0.2 Hz respectively. Meanwhile, odd harmonics were manifested in water hammer oscillation segment, with the harmonic frequencies ranging approximately from 0.07 to 0.75 Hz. Whereas integer harmonics were observed in pre-shut-in segment, ranging from 6 to 40 Hz. The other aspect, the energy distribution of water hammer signals was analyzed in different frequency ranges. In 0-1 Hz, an exponential decay was observed in all three segments. In 1-100 Hz, a periodical energy distribution was observed in pre-shut-in segment, an exponential decay was observed in water hammer oscillation, and an even energy distribution was observed in leak-off segment. In 100-500 Hz, an even energy distribution was observed in those three segments, yet the highest magnitude was noted in leak-off segment. In this study, the effective frequency range and energy distribution characteristics of the field-sampled water hammer signals in different segments were sufficiently elucidated quantitatively and qualitatively for the first time, laying the groundwork for optimizing the filtering parameters of the field filtering models and advancing the accuracy of identifying downhole event locations.
文摘AIM: To investigate the efficacy of Ferrara rings (FR) implantation in the treatment of keratoconus.METHODS: It was a retrospective case series descriptive study. The sample was comprised of 50 patients 79 eyes diagnosed with progressive keratoconus. This included 24 (48%) males and 26 (52%) females between the age of 13 and 44 years. All participants underwent surgical implantation of FR in the period between January 2009 and September 2010 at Jordan University Hospital. Thorough ophthalmologic examinations were applied to measure vital variables for each pathological condition before and after surgery. RESULTS: Findings indicated an overall significant postoperative improvement in both uncorrected visual acuity (UCVA) and best spectacle corrected visual acuity (BSCVA) throughout follow up visits. Moreover, results illustrated a significant decrease in spherical equivalent (SE) and keratometric readings (lower, higher and the average). CONCLUSION: Surgical intervention strategies are being frequently developed to meet the needs of patients with keratoconus. The implantation of Ferrara rings has proven to be a safe and feasible alternative procedure for the treatment of mild-moderate keratoconus especially for patients with contact lenses intolerance. We have found that this procedure has improved visual outcomes in all eyes studied. Nevertheless, further research is needed to investigate long term outcomes.
基金Supported by Key Technologies R &D Program of Guangdong Province (2009B0203030092006B20201007)~~
文摘[Objective] The aim was to study the conditions of tissue culture regeneration seedling by using the stem segments of Euphorbia tirucalli and determine the optimum culture condition of each culture stage,so as to provide references for the factory production and relative study of tissue culture seedling of E. tirucalli. [Method] Taking the stem segments of E. tirucalli as explants,the effects of various mediums on germination rate,multiplication coefficient and rooting rate were studied. [Result] The optimum induction medium of germination culture was 1/2MS＋NAA 0.02 mg/L＋6-BA 1.0 mg/L,with differentiation rate of 89.7%; the best subculture medium was 1/2MS＋NAA 0.02 mg/L＋6-BA 0.60 mg/L＋AD 3.0 mg/L,with multiplication coefficient of 5.70; the optimum rooting culture medium was 1/2MS＋NAA 0.40 mg/L＋IBA 0.4 mg/L,with rooting rate of 100% and transplanting survival rate of 80%. [Conclusion] The tissue culture conditions of stem segments of E. tirucalli were determined primarily.
文摘Advanced traffic monitoring systems encounter substantial challenges in vehicle detection and classification due to the limitations of conventional methods,which often demand extensive computational resources and struggle with diverse data acquisition techniques.This research presents a novel approach for vehicle classification and recognition in aerial image sequences,integrating multiple advanced techniques to enhance detection accuracy.The proposed model begins with preprocessing using Multiscale Retinex(MSR)to enhance image quality,followed by Expectation-Maximization(EM)Segmentation for precise foreground object identification.Vehicle detection is performed using the state-of-the-art YOLOv10 framework,while feature extraction incorporates Maximally Stable Extremal Regions(MSER),Dense Scale-Invariant Feature Transform(Dense SIFT),and Zernike Moments Features to capture distinct object characteristics.Feature optimization is further refined through a Hybrid Swarm-based Optimization algorithm,ensuring optimal feature selection for improved classification performance.The final classification is conducted using a Vision Transformer,leveraging its robust learning capabilities for enhanced accuracy.Experimental evaluations on benchmark datasets,including UAVDT and the Unmanned Aerial Vehicle Intruder Dataset(UAVID),demonstrate the superiority of the proposed approach,achieving an accuracy of 94.40%on UAVDT and 93.57%on UAVID.The results highlight the efficacy of the model in significantly enhancing vehicle detection and classification in aerial imagery,outperforming existing methodologies and offering a statistically validated improvement for intelligent traffic monitoring systems compared to existing approaches.
基金supported by Institute of Information&Communications Technology Planning&Evaluation(IITP)under the Metaverse Support Program to Nurture the Best Talents(IITP-2024-RS-2023-00254529)grant funded by the Korea government(MSIT).
文摘Brain tumors require precise segmentation for diagnosis and treatment plans due to their complex morphology and heterogeneous characteristics.While MRI-based automatic brain tumor segmentation technology reduces the burden on medical staff and provides quantitative information,existing methodologies and recent models still struggle to accurately capture and classify the fine boundaries and diverse morphologies of tumors.In order to address these challenges and maximize the performance of brain tumor segmentation,this research introduces a novel SwinUNETR-based model by integrating a new decoder block,the Hierarchical Channel-wise Attention Decoder(HCAD),into a powerful SwinUNETR encoder.The HCAD decoder block utilizes hierarchical features and channelspecific attention mechanisms to further fuse information at different scales transmitted from the encoder and preserve spatial details throughout the reconstruction phase.Rigorous evaluations on the recent BraTS GLI datasets demonstrate that the proposed SwinHCAD model achieved superior and improved segmentation accuracy on both the Dice score and HD95 metrics across all tumor subregions(WT,TC,and ET)compared to baseline models.In particular,the rationale and contribution of the model design were clarified through ablation studies to verify the effectiveness of the proposed HCAD decoder block.The results of this study are expected to greatly contribute to enhancing the efficiency of clinical diagnosis and treatment planning by increasing the precision of automated brain tumor segmentation.
基金provided by the Science Research Project of Hebei Education Department under grant No.BJK2024115.
文摘High-resolution remote sensing images(HRSIs)are now an essential data source for gathering surface information due to advancements in remote sensing data capture technologies.However,their significant scale changes and wealth of spatial details pose challenges for semantic segmentation.While convolutional neural networks(CNNs)excel at capturing local features,they are limited in modeling long-range dependencies.Conversely,transformers utilize multihead self-attention to integrate global context effectively,but this approach often incurs a high computational cost.This paper proposes a global-local multiscale context network(GLMCNet)to extract both global and local multiscale contextual information from HRSIs.A detail-enhanced filtering module(DEFM)is proposed at the end of the encoder to refine the encoder outputs further,thereby enhancing the key details extracted by the encoder and effectively suppressing redundant information.In addition,a global-local multiscale transformer block(GLMTB)is proposed in the decoding stage to enable the modeling of rich multiscale global and local information.We also design a stair fusion mechanism to transmit deep semantic information from deep to shallow layers progressively.Finally,we propose the semantic awareness enhancement module(SAEM),which further enhances the representation of multiscale semantic features through spatial attention and covariance channel attention.Extensive ablation analyses and comparative experiments were conducted to evaluate the performance of the proposed method.Specifically,our method achieved a mean Intersection over Union(mIoU)of 86.89%on the ISPRS Potsdam dataset and 84.34%on the ISPRS Vaihingen dataset,outperforming existing models such as ABCNet and BANet.
文摘This systematic review aims to comprehensively examine and compare deep learning methods for brain tumor segmentation and classification using MRI and other imaging modalities,focusing on recent trends from 2022 to 2025.The primary objective is to evaluate methodological advancements,model performance,dataset usage,and existing challenges in developing clinically robust AI systems.We included peer-reviewed journal articles and highimpact conference papers published between 2022 and 2025,written in English,that proposed or evaluated deep learning methods for brain tumor segmentation and/or classification.Excluded were non-open-access publications,books,and non-English articles.A structured search was conducted across Scopus,Google Scholar,Wiley,and Taylor&Francis,with the last search performed in August 2025.Risk of bias was not formally quantified but considered during full-text screening based on dataset diversity,validation methods,and availability of performance metrics.We used narrative synthesis and tabular benchmarking to compare performance metrics(e.g.,accuracy,Dice score)across model types(CNN,Transformer,Hybrid),imaging modalities,and datasets.A total of 49 studies were included(43 journal articles and 6 conference papers).These studies spanned over 9 public datasets(e.g.,BraTS,Figshare,REMBRANDT,MOLAB)and utilized a range of imaging modalities,predominantly MRI.Hybrid models,especially ResViT and UNetFormer,consistently achieved high performance,with classification accuracy exceeding 98%and segmentation Dice scores above 0.90 across multiple studies.Transformers and hybrid architectures showed increasing adoption post2023.Many studies lacked external validation and were evaluated only on a few benchmark datasets,raising concerns about generalizability and dataset bias.Few studies addressed clinical interpretability or uncertainty quantification.Despite promising results,particularly for hybrid deep learning models,widespread clinical adoption remains limited due to lack of validation,interpretability concerns,and real-world deployment barriers.
基金supported by the National Natural Science Foundation of China[grant number 62376217]the Young Elite Scientists Sponsorship Program by CAST[grant number 2023QNRC001]the Joint Research Project for Meteorological Capacity Improvement[grant number 24NLTSZ003]。
文摘Deep learning-based methods have become alternatives to traditional numerical weather prediction systems,offering faster computation and the ability to utilize large historical datasets.However,the application of deep learning to medium-range regional weather forecasting with limited data remains a significant challenge.In this work,three key solutions are proposed:(1)motivated by the need to improve model performance in data-scarce regional forecasting scenarios,the authors innovatively apply semantic segmentation models,to better capture spatiotemporal features and improve prediction accuracy;(2)recognizing the challenge of overfitting and the inability of traditional noise-based data augmentation methods to effectively enhance model robustness,a novel learnable Gaussian noise mechanism is introduced that allows the model to adaptively optimize perturbations for different locations,ensuring more effective learning;and(3)to address the issue of error accumulation in autoregressive prediction,as well as the challenge of learning difficulty and the lack of intermediate data utilization in one-shot prediction,the authors propose a cascade prediction approach that effectively resolves these problems while significantly improving model forecasting performance.The method achieves a competitive result in The East China Regional AI Medium Range Weather Forecasting Competition.Ablation experiments further validate the effectiveness of each component,highlighting their contributions to enhancing prediction performance.
基金National Science and Technology Council,the Republic of China,under grants NSTC 113-2221-E-194-011-MY3 and Research Center on Artificial Intelligence and Sustainability,National Chung Cheng University under the research project grant titled“Generative Digital Twin System Design for Sustainable Smart City Development in Taiwan.
文摘Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0.Manual inspection of products on assembly lines remains inefficient,prone to errors and lacks consistency,emphasizing the need for a reliable and automated inspection system.Leveraging both object detection and image segmentation approaches,this research proposes a vision-based solution for the detection of various kinds of tools in the toolkit using deep learning(DL)models.Two Intel RealSense D455f depth cameras were arranged in a top down configuration to capture both RGB and depth images of the toolkits.After applying multiple constraints and enhancing them through preprocessing and augmentation,a dataset consisting of 3300 annotated RGB-D photos was generated.Several DL models were selected through a comprehensive assessment of mean Average Precision(mAP),precision-recall equilibrium,inference latency(target≥30 FPS),and computational burden,resulting in a preference for YOLO and Region-based Convolutional Neural Networks(R-CNN)variants over ViT-based models due to the latter’s increased latency and resource requirements.YOLOV5,YOLOV8,YOLOV11,Faster R-CNN,and Mask R-CNN were trained on the annotated dataset and evaluated using key performance metrics(Recall,Accuracy,F1-score,and Precision).YOLOV11 demonstrated balanced excellence with 93.0%precision,89.9%recall,and a 90.6%F1-score in object detection,as well as 96.9%precision,95.3%recall,and a 96.5%F1-score in instance segmentation with an average inference time of 25 ms per frame(≈40 FPS),demonstrating real-time performance.Leveraging these results,a YOLOV11-based windows application was successfully deployed in a real-time assembly line environment,where it accurately processed live video streams to detect and segment tools within toolkits,demonstrating its practical effectiveness in industrial automation.The application is capable of precisely measuring socket dimensions by utilising edge detection techniques on YOLOv11 segmentation masks,in addition to detection and segmentation.This makes it possible to do specification-level quality control right on the assembly line,which improves the ability to examine things in real time.The implementation is a big step forward for intelligent manufacturing in the Industry 4.0 paradigm.It provides a scalable,efficient,and accurate way to do automated inspection and dimensional verification activities.
文摘Bus and any other public transit connectivity issues facilitate an understanding of the importance of transit planning in enhancing existing or new transit services.Improving transit connectivity is one of the most vital tasks in transit-operations planning.A poor connection can cause some passengers to stop using the transit service.Service-design criteria always contain postulates to improve routing and scheduling coordination(intra-and inter-agency transfer centers/points and synchronized/timed transfers).Ostensibly the lack of well-defined connectivity measures precludes the weighing and quantifying of the result of any coordination effort.This work provides an initial methodological framework and concepts for(1)quantifying transit connectivity measures and(2)directions and tools for detecting weak segments in inter-route and inter-modal chains(paths)for possible revisions/changes.
文摘BACKGROUND Radical resection is an important treatment method for hepatic echinococcosis.The posterosuperior segments of the liver remain the most challenging region for laparoscopic or robotic hepatectomy.AIM To demonstrate the safety and preliminary experience of robotic radical resection of cystic and alveolar echinococcosis in posterosuperior liver segments.METHODS A retrospective analysis was conducted on the clinical data of 5 patients with a median age of 37 years(21-56 years)with cystic and alveolar echinococcosis in difficult liver lesions admitted to two centers from September to December 2019.The surgical methods included total pericystectomy,segmental hepatectomy,or hemihepatectomy.RESULTS Among the 5 patients,4 presented with cystic echinococcosis and 1 presented with alveolar echinococcosis,all of whom underwent robotic radical operation successfully without conversion to laparotomy.Total caudate lobectomy was performed in 2 cases,hepatectomy of segment Ⅶ in 1 case,total pericystectomy of segment Ⅷ in 1 case,and right hemihepatectomy in 1 case.Operation time was 225 min(175-300 min);blood loss was 100 mL(50-600 mL);and postoperative hospital stay duration was 10 d(5-19 d).The Clavien-Dindo complication grade was Ⅰ in 4 cases and Ⅱ in 1 case.No recurrence of echinococcosis was found in any patient at the 3 mo of follow-up.CONCLUSION Robotic radical surgery for cystic and selected alveolar echinococcosis in posterosuperior liver segments is safe and feasible.
基金supported in part by the National Basic Research Program(Nos.2012CB944803 and 2011CB 100202)the National Natural Science Foundation(No.31071383)+1 种基金the National Special Program for Transgenic Research(No. 2009ZX08009-008B)the Priority Academic Program Development from Jiangsu Government of China
文摘Chromosome segment substitution lines（CSSLs） are useful for the precise mapping of quantitative trait loci（QTLs） and dissection of the genetic basis of complex traits.In this study,two whole-genome sequenced rice cultivars,the japonica Nipponbare and indica 9311 were used as recipient and donor,respectively.A population with 57 CSSLs was developed after crossing and back-crossing assisted by molecular markers, and genotypes were identified using a high-throughput resequencing strategy.Detailed graphical genotypes of 38 lines were constructed based on resequencing data.These CSSLs had a total of 95 substituted segments derived from indica 9311,with an average of about 2.5 segments per CSSL and eight segments per chromosome,and covered about 87.4%of the rice whole genome.A multiple linear regression QTL analysis mapped four QTLs for 1000-grain weight.The largest-effect QTL was located in a region on chromosome 5 that contained a cloned major QTL GW5/qSW5 for grain size in rice.These CSSLs with a background of Nipponbare may provide powerful tools for future whole-genome
基金Project supported by National High-Technology Research andDevelopment Program of China (Grant No .2002AA234021)
文摘Tmnsmembrane（TM） protein plays an important role in the life activity of the cells, and the prediction of transmembrane helical segments （TMHs） is an important subject in the bioinformatics research. Thus far, several prediction methods have been reported, but there are some deficiencies in prediction accuracy and adaptability in these methods. In this paper, a method based on discrete wavelet transform （DWT） was developed to predict the TMHs. Two sets of test data sets containing total 60 protein sequences were utilized to access the effect of the method. Compared with the prediction results of TMHMM2.0 and MEMSAT, the obtained results indicate that the presented method has high prediction accuracy.
文摘Since the great 1303 Hongtong, Shanxi, earthquake of magnitude 8, 700 years have elapsed. To analyze the long-term seismic potential, this paper divides the Taiyuan-Linfen portion of the Shanxi graben system into 5 seismogenic segments. Based on data of historical earthquakes and GPS observation, the authors estimate mean seismic-moment rates and average recurrence intervals of strong earthquakes for the individual segments, and fur-ther analyze relative levels of current stress cumulation on the segments based on mapping b-values along the gra-ben system by using the network seismic data for the recent over 30 years. The main result shows that the Linfen basin segment has an estimated mean seismic-moment rate of 2.211016 Nm/a to 3.031016 Nm/a, and its average recurrence interval for M=7.5 earthquake is estimated to be between 1 560 and 2 140 years. For the Ling-shi-Hongtong segment, the estimated average recurrence interval for M=8 earthquakes is between 4 300 and 5 100 years, equivalent to having a mean moment-rate of 2.581016 Nm/a to 3.101016 Nm/a. The contour map of b-values shows that the two segments of Lingshi-Hongtong and Linfen basin have been being at low or relatively low stress levels, reflecting that since the 1303 M=8 and the 1695 M=7.5 earthquake ruptures, the fault-planes strengths of the both segments have not been resumed yet. And the other two segments, the Houma and the Jiexiu-Fenyang, have relatively high stress levels, and have been already identified as potential risky segments for the coming earthquakes from the analysis combining with the estimated average recurrence intervals of earth-quakes on the both segments.
文摘Deformation and dislocations of segments of shield tunnel in construction stage have apparent effect on tunnel structure stress and even cause local cracks and breakage in tunnel. 3D finite element method was used to analyze two segment ring models under uniform injected pressure: (1) segment ring without wedge-shaped segment, which has 16 types of preinstall erection tolerance; (2) segment ring with wedge-shaped segment, which has no preinstall erection tolerance. The analysis results indicate that different erection tolerances can cause irregular deformation in segment ring under uniform injected pressure, and that the tolerance values are enlarged further. Wedge-shaped segment apparently affects the overall deformation of segment ring without erection tolerances. The uniform injected pressure can cause deformation of ring with wedge-shaped segment irregular, and dislocations also appear in this situation. The stress of segment with erection tolerances is much larger than that of segment without erection tolerances. Enlarging the central angle of wedge-shaped segment can make the irregular deformation and dis- locations of segments smaller. The analysis results also provide basis for erection tolerance control and improvement of segment constitution.
基金Project supported by the National Natural Science Foundation of China(Nos.51578496 and 51878603)the Zhejiang Provincial Natural Science Foundation of China(No.LZ16E080001)。
文摘In this study, we examined the thermal effects throughout the process of the placement of span-scale girder segments on a 6×110-m continuous steel box girder in the Hong Kong-Zhuhai-Macao Bridge. Firstly, when a span-scale girder segment is temporarily stored in the open air, temperature gradients will significantly increase the maximum reaction force on temporary supports and cause local buckling at the bottom of the girder segment. Secondly, due to the temperature difference of the girder segments before and after girth-welding, some residual thermal deflections will appear on the girder segments because the boundary conditions of the structure are changed by the girth-welding. Thirdly, the thermal expansion and thermal bending of girder segments will cause movement and rotation of bearings, which must be considered in setting bearings. We propose control measures for these problems based on finite element method simulation with field-measured temperatures. The local buckling during open-air storage can be avoided by reasonably determining the appropriate positions of temporary supports using analysis of overall and local stresses. The residual thermal deflections can be overcome by performing girth-welding during a period when the vertical temperature difference of the girder is within 1 °C, such as after 22:00. Some formulas are proposed to determine the pre-set distances for bearings, in which the movement and rotation of the bearings due to dead loads and thermal loads are considered. Finally, the feasibility of these control measures in the placement of span-scale girder segments on a real continuous girder was verified: no local buckling was observed during open-air storage;the residual thermal deflections after girth-welding were controlled within 5 mm and the residual pre-set distances of bearings when the whole continuous girder reached its design state were controlled within 20 mm.
文摘BACKGROUND：Previous tissue-engineered nerve studies have focused on artificial nerve and nerve cell cultures.The effects of regeneration chambers with autologous nerve bridging for the repair of nerve defects remain unclear.OBJECTIVE：To explore the feasibility and advantages of chitosan tube bridging autologous nerve segments for repairing 12-mm sciatic nerve defects in rats.DESIGN,TIME AND SETTING：A randomized,controlled,animal study using nerve tissue engineering was performed at the Animal Laboratory and Laboratory of Histology and Embryology,Liaoning Medical University from June 2008 to March 2009.MATERIALS：Chitosan powder was purchased from Jinan Haidebei Marine Bioengineering,China.METHODS：A sciatic nerve segment of approximately 8 mm was excised from the posterior margin of the piriformis muscle of Sprague Dawley rats.The two nerve ends shrank to form a 12-mm defect,and the nerve defect was repaired using a chitosan tube bridging autologous nerve segment （bridge group）,a chitosan tube-encapsulated autologous nerve segment （encapsulation group）,and a chitosan tube alone （chitosan tube alone group）,respectively.MAIN OUTCOME MEASURES：Histological and ultrastructural changes of the injured sciatic nerve;number of regenerated myelinated nerve fibers; nerve conduction velocity; leg muscle atrophy; and sciatic nerve functional index.RESULTS：At 4 months after implantation,the chitosan tube was absorbed.The tube was thin,but maintained the original shape,and vascular proliferation was observed around the tube.In the bridge group,regenerative myelinated nerve fibers were thick and orderly,with a thick myelin sheath and intact axonal structure.The number of myelinated nerve fibers and nerve conduction velocity were significantly greater compared with the other groups （P〈 0.01）.Moreover,nerve and muscle function was significantly improved following chitosan tube bridging autologous nerve segment treatment compared with the other groups （P〈 0.05 or P 〈 0.01）.CONCLUSION：Chitosan tube bridging autologous nerve segments exhibited better repair effects on nerve defects compared with chitosan tubeencapsulated autologous nerve segments and a chitosan tube alone.This method provided a simple and effective treatment for long-segmental nerve defects.
