The local dynamical behaviors of a four-dimensional hyperchaotic Lorenz system, including stability and bifurcations, are investigated in this paper by analytical and numerical methods. The equilibriums and their stab...The local dynamical behaviors of a four-dimensional hyperchaotic Lorenz system, including stability and bifurcations, are investigated in this paper by analytical and numerical methods. The equilibriums and their stability under different parameter conditions are analyzed by applying Routh-Hurwitz criterion. The results indicate that the system may exist one, three and five equilibrium points for different system parameters. Based on the central manifold theorem and normal form theorem, the pitchfork bifurcation and Hopf bifurcation are studied respectively. By using the Hopf bifurcation theorem and calculating the first Lyapunov coefficient, the Hopf bifurcation of this system is obtained as supercritical for certain parameters. Finally, the results of theoretical parts are verified by some numerical simulations.展开更多
Recent studies have shown that fibrotic scar formation following cerebral ischemic injury has varying effects depending on the microenvironment.However,little is known about how fibrosis is induced and regulated after...Recent studies have shown that fibrotic scar formation following cerebral ischemic injury has varying effects depending on the microenvironment.However,little is known about how fibrosis is induced and regulated after cerebral ischemic injury.Sonic hedgehog signaling participates in fibrosis in the heart,liver,lung,and kidney.Whether Shh signaling modulates fibrotic scar formation after cerebral ischemic stroke and the underlying mechanisms are unclear.In this study,we found that Sonic Hedgehog expression was upregulated in patients with acute ischemic stroke and in a middle cerebral artery occlusion/reperfusion injury rat model.Both Sonic hedgehog and Mitofusin 2 showed increased expression in the middle cerebral artery occlusion rat model and in vitro fibrosis cell model induced by transforming growth factor-beta 1.Activation of the Sonic hedgehog signaling pathway enhanced the expression of phosphorylated Smad 3 and Mitofusin 2 proteins,promoted the formation of fibrotic scars,protected synapses or promoted synaptogenesis,alleviated neurological deficits following middle cerebral artery occlusion/reperfusion injury,reduced cell apoptosis,facilitated the transformation of meninges fibroblasts into myofibroblasts,and enhanced the proliferation and migration of meninges fibroblasts.The Smad3 phosphorylation inhibitor SIS3 reversed the effects induced by Sonic hedgehog signaling pathway activation.Bioinformatics analysis revealed significant correlations between Sonic hedgehog and Smad3,between Sonic hedgehog and Mitofusin 2,and between Smad3 and Mitofusin 2.These findings suggest that Sonic hedgehog signaling may influence Mitofusin 2 expression by regulating Smad3 phosphorylation,thereby modulating the formation of early fibrotic scars following cerebral ischemic stroke and affecting prognosis.The Sonic Hedgehog signaling pathway may serve as a new therapeutic target for stroke treatment.展开更多
BACKGROUND The standard treatment of transitional cell carcinoma of the upper urinary tract consists of radical nephroureterectomy with bladder cuff removal,which can be performed either in open or laparoscopy or robo...BACKGROUND The standard treatment of transitional cell carcinoma of the upper urinary tract consists of radical nephroureterectomy with bladder cuff removal,which can be performed either in open or laparoscopy or robot-assisted laparoscopy.Treatment of chronic renal insufficiency patients with upper urothelial tumor is in a dilemma.Urologists weigh and consider the balance between tumor control and effective renal function preservation.European Association of Urology guidelines recommend that select patients may benefit from endoscopic treatment,but laparoscopic treatment is rarely reported.CASE SUMMARY In this case report,we describe a case of 79-year-old female diagnosed with urothelial carcinoma of the renal pelvis and adrenal adenoma with chronic renal insufficiency.The patient was treated with retroperitoneal laparoscopic partial resection of the renal pelvis and adrenal adenoma resection simultaneously.CONCLUSION Retroperitoneal laparoscopic partial resection of the renal pelvis is an effective surgical procedure for the treatment of urothelial carcinoma of the renal pelvis.展开更多
Objective:Neoadjuvant therapy(NAT)has become the standard treatment option for patients with locally advanced breast cancer.How to non-invasively screen out patients with pathological complete response(pCR)after NAT h...Objective:Neoadjuvant therapy(NAT)has become the standard treatment option for patients with locally advanced breast cancer.How to non-invasively screen out patients with pathological complete response(pCR)after NAT has become an urgent world-wide clinical problem.Our work aims to the assessment of neoadjuvant treatment response in breast cancer patients for higher accuracy prediction using innovative artificial intelligence system.Methods:In this study,we retrospectively collected longitudinal(pre-NAT and post-NAT)multi-parametric magnetic resonance imaging(MRI)and clinicopathologic data of a total of 1,315 breast cancer patients(clinical stageⅠ-Ⅲ)who had undergone NAT followed by standard surgery and treated across 5 independent medical centers from January 2010 to January 2023.We used radiomics,3D convolutional neural network technology and clinical data statistical analysis methods to extract and screen multimodal features,and then developed and validated a Clinical-Radiomics-Deep-Learning(CRDL)model to predict patients'pCR outcomes based on multimodal fusion features.Results:We use the area under the receiver operating characteristic curve(AUC)in the primary cohort(PC)and3 external validation cohorts(VC_(1-3))to evaluate the model performance.The results showed that the AUC in the PC composed of 2 medical centers was 0.947[95%confidence interval(95%CI):0.931-0.960],and the AUC values in VC_(1-3)were 0.857(95%CI:0.810-0.901),0.883(95%CI:0.841-0.918)and 0.904(95%CI:0.860-0.941),respectively.Conclusions:The CRDL model demonstrated high accuracy and robustness in predicting pCR to NAT using multimodal fusion data.This study provides a strong foundation for non-invasive assessment of pCR status in breast cancer patients following NAT and offers critical insights to guide clinical decision-making in post-NAT treatment planning.展开更多
Natural forests are the primary carbon sinks within terrestrial ecosystems,playing a crucial role in mitigating global climate change.China has successfully restored its natural forest area through extensive protectiv...Natural forests are the primary carbon sinks within terrestrial ecosystems,playing a crucial role in mitigating global climate change.China has successfully restored its natural forest area through extensive protective measures.However,the aboveground carbon(AGC)stock potential of China's natural forests remains considerably uncertain in spatial and temporal dynamics.In this study,we provide a spatially detailed estimation of the maximum AGC stock potential for China's natural forests by integrating high-resolution multi-source remote sensing and field survey data.The analysis reveals that China's natural forests could sequester up to 9.880.10 Pg C by 2030,potentially increasing to 10.460.11 Pg C by 2060.Despite this,the AGC sequestration rate would decline from 0.190.001 to 0.080.001 Pg C·yr^(-1)over the period.Spatially,the future AGC accumulation rates exhibit marked heterogeneity.The warm temperate deciduous broadleaf forest region with predominantly young natural forests,is expected to exhibit the most significant increase of 26.36%by 2060,while the Qinghai-Tibet Plateau Alpine region comprising mainly mature natural forests would exhibit only a 0.74%increase.To sustain the high carbon sequestration capacity of China's natural forests,it is essential to prioritize protecting mature forests alongside preserving and restoring young natural forest areas.展开更多
The tumor microenvironment(TME)-activatable probes have proven effective in enhancing the signalto-background ratio(SBR)for precise fluorescence imaging in tumor diagnosis.However,many fluorophores have suboptimal emi...The tumor microenvironment(TME)-activatable probes have proven effective in enhancing the signalto-background ratio(SBR)for precise fluorescence imaging in tumor diagnosis.However,many fluorophores have suboptimal emission spectra and a short Stokes shift,which may lead to overlap with bioautofluorescence,excitation,and emission spectra,limiting their use in intraoperative guidance.Herein,aγ-glutathione(GSH)responsive near-infrared(NIR)BODIPY probe,named“Pro-Dye”was synthesized with a large Stokes shift of 91 nm.The Pro-Dye can be rapidly and specifically activated by high concentrations of GSH both in solution and inside cancer cells,while remaining inactive in normal cells(Human umbilical vein endothelial cells,HUVECs).The Pro-Dye was further encapsulated by 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-(polyethylene glycol)-5000(DSPE-PEG5000)to form Pro-Dye nanoparticles(NPs),making it water-dispersible for in vivo application.In vivo fluorescence imaging demonstrated that Pro-Dye NPs can accumulate at the tumor and exhibit an improved SBR compared to the“alwayson”probe(Dye NPs).Moreover,the tumor can be precisely resected under the real-time guidance of fluorescence imaging of Pro-Dye NPs,showing a well-defined tumor margin.展开更多
Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on co...Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on complex signal processing algorithms and lack multi-source data analysis.Driven by multi-source measurement data,including the axle box,the bogie frame and the carbody accelerations,this paper proposes a track irregularities monitoring network(TIMNet)based on deep learning methods.TIMNet uses the feature extraction capability of convolutional neural networks and the sequence map-ping capability of the long short-term memory model to explore the mapping relationship between vehicle accelerations and track irregularities.The particle swarm optimization algorithm is used to optimize the network parameters,so that both the vertical and lateral track irregularities can be accurately identified in the time and spatial domains.The effectiveness and superiority of the proposed TIMNet is analyzed under different simulation conditions using a vehicle dynamics model.Field tests are conducted to prove the availability of the proposed TIMNet in quantitatively monitoring vertical and lateral track irregularities.Furthermore,comparative tests show that the TIMNet has a better fitting degree and timeliness in monitoring track irregularities(vertical R2 of 0.91,lateral R2 of 0.84 and time cost of 10 ms),compared to other classical regression.The test also proves that the TIMNet has a better anti-interference ability than other regression models.展开更多
As a major worldwide issue,desertification poses significant threats to ecosystem stability and long-term socioeconomic growth.Within China,the Mu Us Sandy land represents a crucial region for studying desertification...As a major worldwide issue,desertification poses significant threats to ecosystem stability and long-term socioeconomic growth.Within China,the Mu Us Sandy land represents a crucial region for studying desertification phenomena.Comprehending how desertification risks are distributed spatially and what mechanisms drive them remains fundamental for implementing effective strategies in land management and risk mitigation.Our research evaluated desertification vulnerability across the Mu Us Sandy land by applying the MEDALUS model,while investigating causal factors via geographical detector methodology.Findings indicated that territories with high desertification vulnerability extend across 71,401.7 km^(2),constituting 76.87%of the entire region,while zones facing extreme desertification hazard cover 20,578.9 km^(2)(22.16%),primarily concentrated in a band-like pattern along the western boundary of the Mu Us Sandy land.Among the four primary indicators,management quality emerged as the most significant driver of desertification susceptibility,followed by vegetation quality and soil quality.Additionally,drought resistance,land use intensity,and erosion protection were identified as the key factors driving desertification sensitivity.The investigation offers significant theoretical perspectives that can guide the formulation of enhanced strategies for controlling desertification and promoting sustainable land resource utilization within the Mu Us Sandy land region.展开更多
Water stress is expected to intensify due to escalating atmospheric and surface dryness under global warming.Despite extensive research indicate that intensified dryness exacerbates water constraints on ecosystems,the...Water stress is expected to intensify due to escalating atmospheric and surface dryness under global warming.Despite extensive research indicate that intensified dryness exacerbates water constraints on ecosystems,the dynamics and underlying mechanisms of surface water stress(SWS)under climate change remain poorly understood.In this study,we use annual evaporative stress as the surface water stress index(WSI)and provide a comprehensive analysis of historical and projected global terrestrial SWS,covering its characteristic changes,driving factors,and impacts on vegetation.Our results show a significant declining trend in WSI during 1982–2014(-0.0033/decade,p<0.01),indicating the enhancement of SWS concurrent with a rapid expansion of water stress intensified areas at a rate of 1.85%/decade(p<0.01).Using the Budyko-Penman budget framework,we found that the intensification of SWS was primarily driven by an increase in vapor pressure deficit(VPD)and a decrease in precipitation.Furthermore,the intensification of SWS contributed to a decline in vegetation growth,with the extent of areas experiencing increased vegetation water deficit expanding rapidly at a rate of 1.38%per decade(p<0.01).In the future,SWS is projected to escalate,with the proportion of areas experiencing intensified SWS increasing from 6.3%to 24.3%by the end of the century under the SSP5–8.5.Our study provides a comprehensive analysis of the drivers of SWS under climate change and its impacts on ecosystems,offering valuable scientific insights for the effective management of water resources.展开更多
Accurate medical image segmentation plays a crucial role in improving the precision of computer-aided diagnosis.However,complex boundary shapes,low contrast and blurred anatomical structures make fine-grained segmenta...Accurate medical image segmentation plays a crucial role in improving the precision of computer-aided diagnosis.However,complex boundary shapes,low contrast and blurred anatomical structures make fine-grained segmentation a challenging task.Variational Bayesian inference quantifies uncertainty through probability distributions and can construct robust probabilistic models for the boundaries of ambiguous organs and tissues.In this paper,we apply variational Bayesian inference to medical image segmentation and propose variational attention to model the uncertainty of low-contrast and blurry tissue and organ boundaries.This enhances the model's ability to perceive segmentation boundaries,improving robustness and segmentation accuracy.Variational attention first estimates the parameters of the probability distribution of latent representations based on input features.Then,it samples latent representations from the learnt distribution to generate attention weights that optimise the interaction between global features and ambiguous boundaries.We integrate variational attention into the U-Net model by replacing its skip connections,constructing a multi-scale variational attention segmentation model(V-UNet).Experiments on the ISBI 2012 and MoNuSeg 2018 datasets show that our method achieves Dice scores of 95.89%and 82.18%,respectively.Moreover,we integrate V-UNet into the Mask R-CNN framework by replacing the FPN feature extraction head and propose a two-stage segmentation method.Compared to the original Mask R-CNN,our method improves the Dice score by 0.81%,mAP by 8.06%and F1 score by 0.51%.展开更多
文摘The local dynamical behaviors of a four-dimensional hyperchaotic Lorenz system, including stability and bifurcations, are investigated in this paper by analytical and numerical methods. The equilibriums and their stability under different parameter conditions are analyzed by applying Routh-Hurwitz criterion. The results indicate that the system may exist one, three and five equilibrium points for different system parameters. Based on the central manifold theorem and normal form theorem, the pitchfork bifurcation and Hopf bifurcation are studied respectively. By using the Hopf bifurcation theorem and calculating the first Lyapunov coefficient, the Hopf bifurcation of this system is obtained as supercritical for certain parameters. Finally, the results of theoretical parts are verified by some numerical simulations.
基金supported by the National Natural Science Foundation of China,Nos.82171456(to QY)and 81971229(to QY)the Natural Science Foundation of Chongqing,Nos.CSTC2021JCYJ-MSXMX0263(to QY)and CSTB2023NSCQ-MSX1015(to XL)Doctoral Innovation Project of The First Affiliated Hospital of Chongqing Medical University,Nos.CYYY-BSYJSCXXM-202318(to JW)and CYYY-BSYJSCXXM-202327(to HT).
文摘Recent studies have shown that fibrotic scar formation following cerebral ischemic injury has varying effects depending on the microenvironment.However,little is known about how fibrosis is induced and regulated after cerebral ischemic injury.Sonic hedgehog signaling participates in fibrosis in the heart,liver,lung,and kidney.Whether Shh signaling modulates fibrotic scar formation after cerebral ischemic stroke and the underlying mechanisms are unclear.In this study,we found that Sonic Hedgehog expression was upregulated in patients with acute ischemic stroke and in a middle cerebral artery occlusion/reperfusion injury rat model.Both Sonic hedgehog and Mitofusin 2 showed increased expression in the middle cerebral artery occlusion rat model and in vitro fibrosis cell model induced by transforming growth factor-beta 1.Activation of the Sonic hedgehog signaling pathway enhanced the expression of phosphorylated Smad 3 and Mitofusin 2 proteins,promoted the formation of fibrotic scars,protected synapses or promoted synaptogenesis,alleviated neurological deficits following middle cerebral artery occlusion/reperfusion injury,reduced cell apoptosis,facilitated the transformation of meninges fibroblasts into myofibroblasts,and enhanced the proliferation and migration of meninges fibroblasts.The Smad3 phosphorylation inhibitor SIS3 reversed the effects induced by Sonic hedgehog signaling pathway activation.Bioinformatics analysis revealed significant correlations between Sonic hedgehog and Smad3,between Sonic hedgehog and Mitofusin 2,and between Smad3 and Mitofusin 2.These findings suggest that Sonic hedgehog signaling may influence Mitofusin 2 expression by regulating Smad3 phosphorylation,thereby modulating the formation of early fibrotic scars following cerebral ischemic stroke and affecting prognosis.The Sonic Hedgehog signaling pathway may serve as a new therapeutic target for stroke treatment.
文摘BACKGROUND The standard treatment of transitional cell carcinoma of the upper urinary tract consists of radical nephroureterectomy with bladder cuff removal,which can be performed either in open or laparoscopy or robot-assisted laparoscopy.Treatment of chronic renal insufficiency patients with upper urothelial tumor is in a dilemma.Urologists weigh and consider the balance between tumor control and effective renal function preservation.European Association of Urology guidelines recommend that select patients may benefit from endoscopic treatment,but laparoscopic treatment is rarely reported.CASE SUMMARY In this case report,we describe a case of 79-year-old female diagnosed with urothelial carcinoma of the renal pelvis and adrenal adenoma with chronic renal insufficiency.The patient was treated with retroperitoneal laparoscopic partial resection of the renal pelvis and adrenal adenoma resection simultaneously.CONCLUSION Retroperitoneal laparoscopic partial resection of the renal pelvis is an effective surgical procedure for the treatment of urothelial carcinoma of the renal pelvis.
基金supported by the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences(No.2023-JKCS-23)the Special Research Fund for Central Universities,Peking Union Medical College[No.2022-I2M-C&T-A-014,CAMS Innovation Fund for Medical Sciences(CIFMS)]。
文摘Objective:Neoadjuvant therapy(NAT)has become the standard treatment option for patients with locally advanced breast cancer.How to non-invasively screen out patients with pathological complete response(pCR)after NAT has become an urgent world-wide clinical problem.Our work aims to the assessment of neoadjuvant treatment response in breast cancer patients for higher accuracy prediction using innovative artificial intelligence system.Methods:In this study,we retrospectively collected longitudinal(pre-NAT and post-NAT)multi-parametric magnetic resonance imaging(MRI)and clinicopathologic data of a total of 1,315 breast cancer patients(clinical stageⅠ-Ⅲ)who had undergone NAT followed by standard surgery and treated across 5 independent medical centers from January 2010 to January 2023.We used radiomics,3D convolutional neural network technology and clinical data statistical analysis methods to extract and screen multimodal features,and then developed and validated a Clinical-Radiomics-Deep-Learning(CRDL)model to predict patients'pCR outcomes based on multimodal fusion features.Results:We use the area under the receiver operating characteristic curve(AUC)in the primary cohort(PC)and3 external validation cohorts(VC_(1-3))to evaluate the model performance.The results showed that the AUC in the PC composed of 2 medical centers was 0.947[95%confidence interval(95%CI):0.931-0.960],and the AUC values in VC_(1-3)were 0.857(95%CI:0.810-0.901),0.883(95%CI:0.841-0.918)and 0.904(95%CI:0.860-0.941),respectively.Conclusions:The CRDL model demonstrated high accuracy and robustness in predicting pCR to NAT using multimodal fusion data.This study provides a strong foundation for non-invasive assessment of pCR status in breast cancer patients following NAT and offers critical insights to guide clinical decision-making in post-NAT treatment planning.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFF1300203)the National Natural Science Foundation of China(Grant No.42371329s).
文摘Natural forests are the primary carbon sinks within terrestrial ecosystems,playing a crucial role in mitigating global climate change.China has successfully restored its natural forest area through extensive protective measures.However,the aboveground carbon(AGC)stock potential of China's natural forests remains considerably uncertain in spatial and temporal dynamics.In this study,we provide a spatially detailed estimation of the maximum AGC stock potential for China's natural forests by integrating high-resolution multi-source remote sensing and field survey data.The analysis reveals that China's natural forests could sequester up to 9.880.10 Pg C by 2030,potentially increasing to 10.460.11 Pg C by 2060.Despite this,the AGC sequestration rate would decline from 0.190.001 to 0.080.001 Pg C·yr^(-1)over the period.Spatially,the future AGC accumulation rates exhibit marked heterogeneity.The warm temperate deciduous broadleaf forest region with predominantly young natural forests,is expected to exhibit the most significant increase of 26.36%by 2060,while the Qinghai-Tibet Plateau Alpine region comprising mainly mature natural forests would exhibit only a 0.74%increase.To sustain the high carbon sequestration capacity of China's natural forests,it is essential to prioritize protecting mature forests alongside preserving and restoring young natural forest areas.
基金supported by the Natural Science Foundation of Shaanxi Province(Nos.2023-YBSF-270,2024SF-ZDCYL-02-08)Fundamental Research Funds for the Central Universities(No.xzy022024033)+2 种基金Horizontal Project of the First Affiliated Hospital of Xi’an Jiaotong University(No.202304174)supported by the Opening Project of Structural Optimization and Application of Functional Molecules Key Laboratory of Sichuan Province(No.2023GNFZ-03)The Key Laboratory for Screening and Diagnosis of Maternal and Child Genetic Disease of Health Commission of Jiangxi Province.
文摘The tumor microenvironment(TME)-activatable probes have proven effective in enhancing the signalto-background ratio(SBR)for precise fluorescence imaging in tumor diagnosis.However,many fluorophores have suboptimal emission spectra and a short Stokes shift,which may lead to overlap with bioautofluorescence,excitation,and emission spectra,limiting their use in intraoperative guidance.Herein,aγ-glutathione(GSH)responsive near-infrared(NIR)BODIPY probe,named“Pro-Dye”was synthesized with a large Stokes shift of 91 nm.The Pro-Dye can be rapidly and specifically activated by high concentrations of GSH both in solution and inside cancer cells,while remaining inactive in normal cells(Human umbilical vein endothelial cells,HUVECs).The Pro-Dye was further encapsulated by 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-(polyethylene glycol)-5000(DSPE-PEG5000)to form Pro-Dye nanoparticles(NPs),making it water-dispersible for in vivo application.In vivo fluorescence imaging demonstrated that Pro-Dye NPs can accumulate at the tumor and exhibit an improved SBR compared to the“alwayson”probe(Dye NPs).Moreover,the tumor can be precisely resected under the real-time guidance of fluorescence imaging of Pro-Dye NPs,showing a well-defined tumor margin.
基金supported by the Sichuan Science and Technology Program(Nos.2024JDRC0100 and 2023YFQ0091)the National Natural Science Foundation of China(Nos.U21A20167 and 52475138)the Scientific Research Foundation of the State Key Laboratory of Rail Transit Vehicle System(No.2024RVL-T08).
文摘Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on complex signal processing algorithms and lack multi-source data analysis.Driven by multi-source measurement data,including the axle box,the bogie frame and the carbody accelerations,this paper proposes a track irregularities monitoring network(TIMNet)based on deep learning methods.TIMNet uses the feature extraction capability of convolutional neural networks and the sequence map-ping capability of the long short-term memory model to explore the mapping relationship between vehicle accelerations and track irregularities.The particle swarm optimization algorithm is used to optimize the network parameters,so that both the vertical and lateral track irregularities can be accurately identified in the time and spatial domains.The effectiveness and superiority of the proposed TIMNet is analyzed under different simulation conditions using a vehicle dynamics model.Field tests are conducted to prove the availability of the proposed TIMNet in quantitatively monitoring vertical and lateral track irregularities.Furthermore,comparative tests show that the TIMNet has a better fitting degree and timeliness in monitoring track irregularities(vertical R2 of 0.91,lateral R2 of 0.84 and time cost of 10 ms),compared to other classical regression.The test also proves that the TIMNet has a better anti-interference ability than other regression models.
基金the National Natural Science Foundation of China(Grant No.42301336)the Open Research Fund of Henan Provincial Key Laboratory of Hydrosphere and Watershed Water Security(Grant No.HWWSF202302).
文摘As a major worldwide issue,desertification poses significant threats to ecosystem stability and long-term socioeconomic growth.Within China,the Mu Us Sandy land represents a crucial region for studying desertification phenomena.Comprehending how desertification risks are distributed spatially and what mechanisms drive them remains fundamental for implementing effective strategies in land management and risk mitigation.Our research evaluated desertification vulnerability across the Mu Us Sandy land by applying the MEDALUS model,while investigating causal factors via geographical detector methodology.Findings indicated that territories with high desertification vulnerability extend across 71,401.7 km^(2),constituting 76.87%of the entire region,while zones facing extreme desertification hazard cover 20,578.9 km^(2)(22.16%),primarily concentrated in a band-like pattern along the western boundary of the Mu Us Sandy land.Among the four primary indicators,management quality emerged as the most significant driver of desertification susceptibility,followed by vegetation quality and soil quality.Additionally,drought resistance,land use intensity,and erosion protection were identified as the key factors driving desertification sensitivity.The investigation offers significant theoretical perspectives that can guide the formulation of enhanced strategies for controlling desertification and promoting sustainable land resource utilization within the Mu Us Sandy land region.
基金jointly supported by the National Natural Science Foundation of China(Grant No.U2442207)the Youth Innovation Promotion Association of Chinese Academy of Sciences(Grant No.2021427)+1 种基金the West Light Foundation(Grant No.xbzg-zdsys-202409)of the Chinese Academy of SciencesKey Talent Project in Gansu and Central Guidance Fund for Local Science and Technology Development Projects in Gansu(Grant No.24ZYQA031)。
文摘Water stress is expected to intensify due to escalating atmospheric and surface dryness under global warming.Despite extensive research indicate that intensified dryness exacerbates water constraints on ecosystems,the dynamics and underlying mechanisms of surface water stress(SWS)under climate change remain poorly understood.In this study,we use annual evaporative stress as the surface water stress index(WSI)and provide a comprehensive analysis of historical and projected global terrestrial SWS,covering its characteristic changes,driving factors,and impacts on vegetation.Our results show a significant declining trend in WSI during 1982–2014(-0.0033/decade,p<0.01),indicating the enhancement of SWS concurrent with a rapid expansion of water stress intensified areas at a rate of 1.85%/decade(p<0.01).Using the Budyko-Penman budget framework,we found that the intensification of SWS was primarily driven by an increase in vapor pressure deficit(VPD)and a decrease in precipitation.Furthermore,the intensification of SWS contributed to a decline in vegetation growth,with the extent of areas experiencing increased vegetation water deficit expanding rapidly at a rate of 1.38%per decade(p<0.01).In the future,SWS is projected to escalate,with the proportion of areas experiencing intensified SWS increasing from 6.3%to 24.3%by the end of the century under the SSP5–8.5.Our study provides a comprehensive analysis of the drivers of SWS under climate change and its impacts on ecosystems,offering valuable scientific insights for the effective management of water resources.
基金supported by the China Chongqing Municipal Education Commission(Grant KJZDM202500505)China Chongqing Municipal Science and Technology Bureau(Grants CSTB2024TIADCYKJCXX0009,CSTB2024NSCQ-LZX0043)+1 种基金Chongqing University of Technology graduate education high-quality development project(Grants gzlsz202304,gzlkc202401,gzltd202502)Chongqing University of Technology-Chongqing LINGLUE Technology Co.Ltd.Electronic Information(artificial intelligence)graduate joint training base.
文摘Accurate medical image segmentation plays a crucial role in improving the precision of computer-aided diagnosis.However,complex boundary shapes,low contrast and blurred anatomical structures make fine-grained segmentation a challenging task.Variational Bayesian inference quantifies uncertainty through probability distributions and can construct robust probabilistic models for the boundaries of ambiguous organs and tissues.In this paper,we apply variational Bayesian inference to medical image segmentation and propose variational attention to model the uncertainty of low-contrast and blurry tissue and organ boundaries.This enhances the model's ability to perceive segmentation boundaries,improving robustness and segmentation accuracy.Variational attention first estimates the parameters of the probability distribution of latent representations based on input features.Then,it samples latent representations from the learnt distribution to generate attention weights that optimise the interaction between global features and ambiguous boundaries.We integrate variational attention into the U-Net model by replacing its skip connections,constructing a multi-scale variational attention segmentation model(V-UNet).Experiments on the ISBI 2012 and MoNuSeg 2018 datasets show that our method achieves Dice scores of 95.89%and 82.18%,respectively.Moreover,we integrate V-UNet into the Mask R-CNN framework by replacing the FPN feature extraction head and propose a two-stage segmentation method.Compared to the original Mask R-CNN,our method improves the Dice score by 0.81%,mAP by 8.06%and F1 score by 0.51%.
