Accurate and efficient detection of building changes in remote sensing imagery is crucial for urban planning,disaster emergency response,and resource management.However,existing methods face challenges such as spectra...Accurate and efficient detection of building changes in remote sensing imagery is crucial for urban planning,disaster emergency response,and resource management.However,existing methods face challenges such as spectral similarity between buildings and backgrounds,sensor variations,and insufficient computational efficiency.To address these challenges,this paper proposes a novel Multi-scale Efficient Wavelet-based Change Detection Network(MewCDNet),which integrates the advantages of Convolutional Neural Networks and Transformers,balances computational costs,and achieves high-performance building change detection.The network employs EfficientNet-B4 as the backbone for hierarchical feature extraction,integrates multi-level feature maps through a multi-scale fusion strategy,and incorporates two key modules:Cross-temporal Difference Detection(CTDD)and Cross-scale Wavelet Refinement(CSWR).CTDD adopts a dual-branch architecture that combines pixel-wise differencing with semanticaware Euclidean distance weighting to enhance the distinction between true changes and background noise.CSWR integrates Haar-based Discrete Wavelet Transform with multi-head cross-attention mechanisms,enabling cross-scale feature fusion while significantly improving edge localization and suppressing spurious changes.Extensive experiments on four benchmark datasets demonstrate MewCDNet’s superiority over comparison methods:achieving F1 scores of 91.54%on LEVIR,93.70%on WHUCD,and 64.96%on S2Looking for building change detection.Furthermore,MewCDNet exhibits optimal performance on the multi-class⋅SYSU dataset(F1:82.71%),highlighting its exceptional generalization capability.展开更多
Located downstream the Kupang Catchment in Indonesia,Pekalongan faces significant land subsidence issues,leading to severe coastal flooding.This study aimed to assess the impact of climate change on future flow regime...Located downstream the Kupang Catchment in Indonesia,Pekalongan faces significant land subsidence issues,leading to severe coastal flooding.This study aimed to assess the impact of climate change on future flow regimes and hydrological extremes to inform long-term water resources management strategies for the Kupang Catchment.Utilizing precipitation and air temperature data from general circulation models in the Coupled Model Intercomparison Project 6(CMIP6)and employing bias correction techniques,the Soil and Water Assessment Tool(SWAT)hydrological model was employed to analyze climate-induced changes in hydrological fluxes,specifically streamflow.Results indicated a consistent increase in monthly streamflow during the wet season,with a substantial rise of 22.8%,alongside a slight decrease of 18.0%during the dry season.Moreover,both the frequency and severity of extremely low and high flows were projected to intensify by approximately 50%and 70%,respectively,for a 20-year return period,suggesting heightened flood and drought risks in the future.The observed declining trend in low flow,by up to 11%,indicated the potential for long-term groundwater depletion exacerbating the threat of land subsidence and coastal flooding,especially in areas with inadequate surface water management policies and infrastructure.展开更多
As global greenhouse gases continue rising,the urgency of more ambitious action is clearer than ever before.China is the world’s biggest emitter of greenhouse gases and one of the countries affected most by climate c...As global greenhouse gases continue rising,the urgency of more ambitious action is clearer than ever before.China is the world’s biggest emitter of greenhouse gases and one of the countries affected most by climate change.The evidence about the impacts of climate change on the environment and human health may encourage China to take more decisive action to mitigate greenhouse gas emissions and adapt to climate impacts.展开更多
Latent heat thermal energy storage(TES)effectively reduces the mismatch between energy supply and demand of renewable energy sources by the utilization of phase change materials(PCMs).However,the low thermal conductiv...Latent heat thermal energy storage(TES)effectively reduces the mismatch between energy supply and demand of renewable energy sources by the utilization of phase change materials(PCMs).However,the low thermal conductivity and poor shape stability are the main drawbacks in realizing the large-scale application of PCMs.Promisingly,developing composite PCM(CPCM)based on porous supporting mate-rial provides a desirable solution to obtain performance-enhanced PCMs with improved effective thermal conductivity and shape stability.Among all the porous matrixes as supports for PCM,three-dimensional carbon-based porous supporting material has attracted considerable attention ascribing to its high ther-mal conductivity,desirable loading capacity of PCMs,and excellent chemical compatibility with various PCMs.Therefore,this work systemically reviews the CPCMs with three-dimensional carbon-based porous supporting materials.First,a concise rule for the fabrication of CPCMs is illustrated in detail.Next,the experimental and computational research of carbon nanotube-based support,graphene-based support,graphite-based support and amorphous carbon-based support are reviewed.Then,the applications of the shape-stabilized CPCMs including thermal management and thermal conversion are illustrated.Last but not least,the challenges and prospects of the CPCMs are discussed.To conclude,introducing carbon-based porous materials can solve the liquid leakage issue and essentially improve the thermal conductivity of PCMs.However,there is still a long way to further develop a desirable CPCM with higher latent heat capacity,higher thermal conductivity,and more excellent shape stability.展开更多
Terrestrial ecosystems heavily depend on vegetation,which responds to carbon dioxide(CO_(2))fertilization in hot and humid regions.The subtropical humid karst region is a hot and humid region;whether and to what exten...Terrestrial ecosystems heavily depend on vegetation,which responds to carbon dioxide(CO_(2))fertilization in hot and humid regions.The subtropical humid karst region is a hot and humid region;whether and to what extent CO_(2)fertilization affects vegetation changes in such regions remains unclear.In this study,we investigated the degree to which CO_(2)fertilization influences vegetation changes,along with their spatial and temporal differences,in the subtropical humid karst region using time-lag effect analysis,a random forest model,and multiple regression analysis.Results showed that CO_(2)fertilization plays an important role in vegetation changes,exhibiting clear spatial variations across different geomorphological zones,with its degree of influence ranging mainly between 11%and 25%.The highest contribution of CO_(2)fertilization was observed in the karst basin and non-karstic region,whereas the lowest contribution was found in the karst plateau region.Previous studies have primarily attributed vegetation changes in subtropical humid karst region to ecological engineering,leading to an overestimation of its contribution to these changes.The findings of this study enhance the understanding of the mechanism of vegetation changes in humid karst region and provide theoretical and practical insights for ecological and environmental protection in these regions.展开更多
The toxicity of PM_(2.5)does not necessarily change synchronously with its mass concentration.In this study,the chemical composition(carbonaceous species,water-soluble ions,and metals)and oxidative potential(dithiothr...The toxicity of PM_(2.5)does not necessarily change synchronously with its mass concentration.In this study,the chemical composition(carbonaceous species,water-soluble ions,and metals)and oxidative potential(dithiothreitol assay,DTT)of PM_(2.5)were investigated in 2017/2018 and 2022 in Xiamen,China.The decrease rate of volume-normalized DTT(DTTv)(38%)was lower than that of PM_(2.5)(55%)between the two sampling periods.However,the mass-normalized DTT(DTTm)increased by 44%.Clear seasonal patterns with higher levels in winter were found for PM_(2.5),most chemical constituents and DTTv but not for DTTm.The large decrease in DTT activity(84%−92%)after the addition of EDTA suggested that watersoluble metals were the main contributors to DTT in Xiamen.The increased gap between the reconstructed and measured DTTv and the stronger correlations between the reconstructed/measured DTT ratio and carbonaceous species in 2022were observed.The decrease rates of the hazard index(32.5%)and lifetime cancer risk(9.1%)differed from those of PM_(2.5)and DTTv due to their different main contributors.The PMF-MLR model showed that the contributions(nmol/(min·m^(3)))of vehicle emission,coal+biomass burning,ship emission and secondary aerosol to DTTv in 2022 decreased by 63.0%,65.2%,66.5%,and 22.2%,respectively,compared to those in 2017/2018,which was consistent with the emission reduction of vehicle exhaust and coal consumption,the adoption of low-sulfur fuel oil used on board ships and the reduced production of WSOC.However,the contributions of dust+sea salt and industrial emission increased.展开更多
Agricultural pests cause enormous losses in annual agricultural production.Understanding the evolutionary responses and adaptive capacity of agricultural pests under climate change is crucial for establishing sustaina...Agricultural pests cause enormous losses in annual agricultural production.Understanding the evolutionary responses and adaptive capacity of agricultural pests under climate change is crucial for establishing sustainable and environmentally friendly agricultural pest management.In this study,we integrate climate modeling and landscape genomics to investigate the distributional dynamics of the cotton bollworm(Helicoverpa armigera)in the adaptation to local environments and resilience to future climate change.Notably,the predicted inhabitable areas with higher suitability for the cotton bollworm could be eight times larger in the coming decades.Climate change is one of the factors driving the dynamics of distribution and population differentiation of the cotton bollworm.Approximately 19,000 years ago,the cotton bollworm expanded from its ancestral African population,followed by gradual occupations of the European,Asian,Oceanian,and American continents.Furthermore,we identify seven subpopulations with high dispersal and adaptability which may have an increased risk of invasion potential.Additionally,a large number of candidate genes and SNPs linked to climatic adaptation were mapped.These findings could inform sustainable pest management strategies in the face of climate change,aiding future pest forecasting and management planning.展开更多
BACKGROUND Atypical optic neuritis,consisting of neuromyelitis optica spectrum disorders(NMOSD)or myelin oligodendrocyte glycoprotein antibody disease(MOGAD),has a very similar presentation but different prognostic im...BACKGROUND Atypical optic neuritis,consisting of neuromyelitis optica spectrum disorders(NMOSD)or myelin oligodendrocyte glycoprotein antibody disease(MOGAD),has a very similar presentation but different prognostic implications and longterm management strategies.Vascular and metabolic factors are being thought to play a role in such autoimmune neuro-inflammatory disorders,apart from the obvious immune mediated damage.With the advent of optical coherence tomography angiography(OCTA),it is easy to pick up on these subclinical macular microvascular and structural changes.AIM To study the macular microvascular and structural changes on OCTA in atypical optic neuritis.METHODS This observational cross-sectional study involved 8 NMOSD and 17 MOGAD patients,diagnosed serologically,as well as 10 healthy controls.Macular vascular density(MVD)and ganglion cell+inner plexiform layer thickness(GCIPL)were studied using OCTA.RESULTS There was a significant reduction in MVD in NMOSD and MOGAD affected as well as unaffected eyes when compared with healthy controls.NMOSD and MOGAD affected eyes had significant GCIPL thinning compared with healthy controls.NMOSD unaffected eyes did not show significant GCIPL thinning compared to healthy controls in contrast to MOGAD unaffected eyes.On comparing NMOSD with MOGAD,there was no significant difference in terms of MVD or GCIPL in the affected or unaffected eyes.CONCLUSION Although significant microvascular and structural changes are present on OCTA between atypical optic neuritis and normal patients,they could not help in differentiating between NMOSD and MOGAD cases.展开更多
Gas-bearing shales have become a major source of future natural gas production worldwide.It has become increasingly urgent to develop a reliable prediction model and corresponding workflow for identifying shale gas sw...Gas-bearing shales have become a major source of future natural gas production worldwide.It has become increasingly urgent to develop a reliable prediction model and corresponding workflow for identifying shale gas sweet spots.The formation of gas-bearing shales is closely linked to relative sealevel changes,providing an important approach to predicting sweet spots in the Wufeng-Longmaxi shale in the southern Sichuan Basin,China.Three types of marine shale gas sweet spots are identified in the shale based on their formation stages combined with relative sea-level changes:early,middle,and late transgression types.This study develops a prediction model and workflow for identifying shale gas sweet spots by analyzing relative sea-level changes and facies sequences.Predicting shale gas sweet spots in an explored block using this model and workflow can provide a valuable guide for well design and hydraulic fracturing,significantly enhancing the efficiency of shale gas exploration and development.Notably,the new prediction model and workflow can be utilized for the rapid evaluation of the potential for shale gas development in new shale gas blocks or those with low exploratory maturity.展开更多
We examine possible funding sources for constructing Climate Change Haven Communities on a global basis. Areas of the planet that have the potential to house persons migrating to “safe havens” in their own or other ...We examine possible funding sources for constructing Climate Change Haven Communities on a global basis. Areas of the planet that have the potential to house persons migrating to “safe havens” in their own or other countries will require the rapid construction of communities capable of supporting them, their families, businesses and farms. However, different political-economic conditions are found across the areas which can serve as locations for these Climate Change Haven Communities. We develop funding and construction strategies for the United States (free-market capitalism), France and Spain (European Union supported economies), and Taiwan region (state-directed economy). The proposals for the Taiwan region should also be applicable to the rest of China.展开更多
Climate change and anthropogenic activities have driven significant terrestrial water storage changes(TWSC)in the Three Rivers Source Region(TRSR),exerting profound impacts on freshwater availability across China and ...Climate change and anthropogenic activities have driven significant terrestrial water storage changes(TWSC)in the Three Rivers Source Region(TRSR),exerting profound impacts on freshwater availability across China and broader Asia.However,long-term TWSC characterization remains challenging due to limited observational data in this alpine region.Here,we integrate GRACE observations(2002-2020),ERA5-Land reanalysis,and GLDAS data to reconstruct TWSC using two methods:(1)the water balance method(PER)and(2)the component summation method(SS),applied to three input datasets(ERA5-Land,GLDAS,and their average,GLER).Comparative analysis reveals that the SS method applied to GL-ER yields the highest consistency with GRACE-derived TWSC.Using this optimal approach,we extend the analysis to 1951~2020,uncovering spatiotemporal TWSC patterns.Although annual TWSC trends appear negligible due to strong seasonality,we introduce the intra-year TWSC fluctuation(TWSCF)index to quantify cumulative variability.A significant(p<0.05)transition occurred in 1980,with TWSCF shifting from a declining trend(-0.39 mm/yr)to an increasing trend(0.56 mm/yr),primarily driven by soil moisture changes.However,Hurst exponent analysis suggests this upward trend may not persist.Drought and vegetation assessments indicate concurrent wetting and greening in the TRSR.TWSC correlates strongly with meteorological drought,acting as a reliable drought indicator while its linkage with vegetation dynamics suggests a potential contribution to greening.Our findings provide a robust framework for understanding long-term TWSC evolution and its hydrological-ecological interactions under climate change.展开更多
BACKGROUND Dyslipidemia was strongly linked to stroke,however the relationship between dyslipidemia and its components and ischemic stroke remained unexplained.AIM To investigate the link between longitudinal changes ...BACKGROUND Dyslipidemia was strongly linked to stroke,however the relationship between dyslipidemia and its components and ischemic stroke remained unexplained.AIM To investigate the link between longitudinal changes in lipid profiles and dyslipidemia and ischemic stroke in a hypertensive population.METHODS Between 2013 and 2014,6094 hypertension individuals were included in this,and ischemic stroke cases were documented to the end of 2018.Longitudinal changes of lipid were stratified into four groups:(1)Normal was transformed into normal group;(2)Abnormal was transformed into normal group;(3)Normal was transformed into abnormal group;and(4)Abnormal was transformed into abnormal group.To examine the link between longitudinal changes in dyslipidemia along with its components and the risk of ischemic stroke,we utilized multivariate Cox proportional hazards models with hazard ratio(HR)and 95%CI.RESULTS The average age of the participants was 62.32 years±13.00 years,with 329 women making up 54.0%of the sample.Over the course of a mean follow-up of 4.8 years,143 ischemic strokes happened.When normal was transformed into normal group was used as a reference,after full adjustments,the HR for dyslipidemia and ischemic stroke among abnormal was transformed into normal group,normal was transformed into abnormal group and abnormal was transformed into abnormal Wei CC et al.Dyslipidemia changed and ischemic stroke WJCC https://www.wjgnet.com 2 February 6,2025 Volume 13 Issue 4 group were 1.089(95%CI:0.598-1.982;P=0.779),2.369(95%CI:1.424-3.941;P<0.001)and 1.448(95%CI:1.002-2.298;P=0.047)(P for trend was 0.233),respectively.CONCLUSION In individuals with hypertension,longitudinal shifts from normal to abnormal in dyslipidemia-particularly in total and low-density lipoprotein cholesterol-were significantly associated with the risk of ischemic stroke.展开更多
We adopted the solution impregnation route with aluminum dihydrogen phosphate solution as liquid medium for effective surface modification on graphite substrate.The mass ratio of graphite to Al(H_(2)PO_(4))_(3) change...We adopted the solution impregnation route with aluminum dihydrogen phosphate solution as liquid medium for effective surface modification on graphite substrate.The mass ratio of graphite to Al(H_(2)PO_(4))_(3) changed from 0.5:1 to 4:1,and the impregnation time changed from 1 to 7 h.The typical composite phase change thermal storage materials doped with the as-treated graphite were fabricated using form-stable technique.To investigate the oxidation and anti-oxidation behavior of the impregnated graphite at high temperatures,the samples were put into a muffle furnace for a cyclic heat test.Based on SEM,EDS,DSC techniques,analyses on the impregnated technique suggested an optimized processing conditions of a 3 h impregnation time with the ratio of graphite:Al(H_(2)PO_(4))_(3) as 1:3 for graphite impregnation treatment.Further investigations on high-temperature phase change heat storage materials doped by the treated graphite suggested excellent oxidation resistance and thermal cycling performance.展开更多
Oriented graphene aerogels have limited applica-tions because the flexibility of their graphene sheets and mi-crostructure give them a low skeleton strength,insufficient compression resilience,and poor flexibility.We ...Oriented graphene aerogels have limited applica-tions because the flexibility of their graphene sheets and mi-crostructure give them a low skeleton strength,insufficient compression resilience,and poor flexibility.We report the preparation of novel aerogel materials with a much better per-formance.Using the driving force of graphene oxide(GO)self-assembly andπ-πinteractions,carbon nanotubes(CNTs)were attached to the GO sheets,and an oriented composite carbon skeleton was constructed using“hydro-plastic foam-ing”.The introduction of CNTs significantly increased the strength of the skeleton and gave the aerogel an excellent re-versible compressibility.The innovative use of cold pressing greatly improved the thermal conductivity and flexibility of the aerogel,providing new ideas for the development of high-performance aerogels.Tests show that the obtained graphene composite aerogel has a reversible compressive strain of over 90%and can withstand 500 compression cycles along the direc-tion of pore accumulation.It can endure more than 10000 bending cycles perpendicular to the direction of composite carbon layer stacking,and its in-plane thermal conductivity reaches 64.5 W·m^(-1)·K^(-1).When filled with phase change materials,the high porosity of the carbon skeleton enables the material to have a high phase change filling rate,and its phase change enthalpy is greater than 150 J/g.Thanks to the exceptional flexibility of the carbon skeleton,the macrostructure of phase change materials can be bent as needed to adapt to thermal management scenarios and conform to device shapes.This significantly enhances practical application compatibility,providing flexible support for temperature control and thermal management across diverse device forms.展开更多
In Niger, farms have been facing negative effects of climate change for several decades. The objective of this work is to assess the vulnerability of farms in Tillabery department by proposing an adaptation approach. ...In Niger, farms have been facing negative effects of climate change for several decades. The objective of this work is to assess the vulnerability of farms in Tillabery department by proposing an adaptation approach. A five-step method and descriptive analysis were used on a sample of 250 farmers. The degree of damage caused by pests and crop diseases is significant, with respective proportions of 52.50% and 40.40%. It appears that the main climate risk factors for vulnerability are droughts, floods, soil degradation, and pest invasions. Additionally, the average level of exposure to agricultural operations is very high, with an index of 0.6. The sensitivity index remained constant in the range of 0.3 to 0.6 and is significant (reaching an index of 0.8). However, 61.2% of farms have a medium level of vulnerability and 33.3% have a high vulnerability to the effects of climate change. Nonetheless, a concerning trend regarding the vulnerability of farms has been observed. To assist policymakers and development actors in improving the vulnerability level of these production units, four phases of action are proposed: a diagnostic phase, evaluation, estimation of adaptation needs, implementation, and proper monitoring of actions.展开更多
The department of Tillabéri is primarily affected by climatic phenomena, impacting crop yields, growing cycles, and consequently, the economic outcomes of agricultural operations. The objective of this study is t...The department of Tillabéri is primarily affected by climatic phenomena, impacting crop yields, growing cycles, and consequently, the economic outcomes of agricultural operations. The objective of this study is to analyze these impacts of climate disruption on the economic performance of farms. The methodology adopted for this study combined documentary research with field surveys conducted on a sample of 250 randomly selected farmers. The analytical methods used mainly consisted of linear regression, profitability calculations, and linear programming. The findings indicate that all productions across different crops have experienced a decrease over the past 30 years. For instance, the production of millet, sorghum, and cowpea, which were respectively 812 kg/ha, 260 kg/ha, and 100 kg/ha between the last 30 and 20 years, has now dropped to 412 kg/ha, 106 kg/ha, and 46 kg/ha respectively. A negative and significant effect on agricultural net margin was observed due to variables such as flooding, drought, pest invasion in rice fields, and temperature changes. Smallholder farms show a relatively low margin (46%) to cover their fixed costs, which may indicate a risk if fixed expenses are high. Furthermore, the analysis results from linear programming reveal that farmers could achieve an additional net profit per hectare of 116,861 FCFA, 217201.5 FCFA, and 291988.2 FCFA respectively for small, medium, and large producers by managing variable costs and health-related expenses for households.展开更多
Objective Primary liver cancer,predominantly hepatocellular carcinoma(HCC),is a significant global health issue,ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality.Accura...Objective Primary liver cancer,predominantly hepatocellular carcinoma(HCC),is a significant global health issue,ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality.Accurate and early diagnosis of HCC is crucial for effective treatment,as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma(ICC)exhibit different prognoses and treatment responses.Traditional diagnostic methods,including liver biopsy and contrast-enhanced ultrasound(CEUS),face limitations in applicability and objectivity.The primary objective of this study was to develop an advanced,lightweighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images.The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions.Methods This retrospective study encompassed a total of 161 patients,comprising 131 diagnosed with HCC and 30 with non-HCC malignancies.To achieve accurate tumor detection,the YOLOX network was employed to identify the region of interest(ROI)on both B-mode ultrasound and CEUS images.A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images.These curves provided critical data for the subsequent analysis and classification process.To analyze the extracted brightness change curves and classify the malignancies,we developed and compared several models.These included one-dimensional convolutional neural networks(1D-ResNet,1D-ConvNeXt,and 1D-CNN),as well as traditional machine-learning methods such as support vector machine(SVM),ensemble learning(EL),k-nearest neighbor(KNN),and decision tree(DT).The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics:area under the receiver operating characteristic(AUC),accuracy(ACC),sensitivity(SE),and specificity(SP).Results The evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM,0.56 for ensemble learning,0.63 for KNN,and 0.72 for the decision tree.These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves.In contrast,the deep learning models demonstrated significantly higher AUCs,with 1D-ResNet achieving an AUC of 0.72,1D-ConvNeXt reaching 0.82,and 1D-CNN obtaining the highest AUC of 0.84.Moreover,under the five-fold cross-validation scheme,the 1D-CNN model outperformed other models in both accuracy and specificity.Specifically,it achieved accuracy improvements of 3.8%to 10.0%and specificity enhancements of 6.6%to 43.3%over competing approaches.The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification.Conclusion The 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies,surpassing both traditional machine-learning methods and other deep learning models.This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’diagnostic capabilities.By improving the accuracy and efficiency of clinical decision-making,this tool has the potential to positively impact patient care and outcomes.Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.展开更多
South Florida’s natural forest ecosystems,including pine rocklands and hardwood hammocks,are threatened by land use change and urbanization,invasive species,and climate change.It is critical to understand the respons...South Florida’s natural forest ecosystems,including pine rocklands and hardwood hammocks,are threatened by land use change and urbanization,invasive species,and climate change.It is critical to understand the responses of these ecosystems to anthropogenic disturbances to conserve the remnants of the USA natural subtropical forests.Using dendrochronology,long-term growth patterns were characterized in three dominant native tree species:Bursera simaruba,Swietenia mahagoni,and Pinus elliottii.Core samples were collected from>30 individuals of each species in hardwood hammocks(B.simaruba and S.mahagoni)and pine rocklands(P.elliottii)to examine growth patterns.Relationships between annual tree growth rates and climatic variables were assessed to address three questions:(1)What are the climatic drivers of growth in these three South Florida tree species?(2)Are their growth rates stable or changing through time?and(3)Are tree growth rates affected by urbanization?Standardized growth rates of the three species have changed through time,with small young trees showing accelerated growth through time,whereas larger,older trees showed declining growth rates.S.mahagoni and B.simaruba grew faster in urbanized parks than in more natural parks,whereas P.elliottii grew slower in urban parks.There were positive correlations between tree growth and the current year’s fall precipitation and no discernable effects of the current year’s monthly temperatures on growth rates of any of the species.These results suggest that the foundational tree species of the southern USA endangered pine rocklands and hardwood hammocks may be vulnerable to ongoing changes in precipitation and temperature as well as other environmental effects associated with urbanization.展开更多
On September 5, 2022, an earthquake of magnitude M_(S)6.8 occurred in Luding County, Sichuan Province.This earthquake occurred at the key part of the southeast-clockwise extrusion of material on the eastern margin of ...On September 5, 2022, an earthquake of magnitude M_(S)6.8 occurred in Luding County, Sichuan Province.This earthquake occurred at the key part of the southeast-clockwise extrusion of material on the eastern margin of the Qinghai Plateau, the Y-shaped confluence of the Xianshuihe, Longmenshan and Anninghe fault zones. In this study, the three-dimensional dynamic crustal density changes in the earthquake area are obtained by the typical gravity change data from 2019 to 2022 before the earthquake and gravity inversion by growing bodies. The results indicate that gravity changes presented an obvious fourquadrant and gradient belt distribution in the Luding area before the earthquake. The threedimensional density horizontal slices show that small density changes occurred at the epicenter in the mid-to-upper crust between 2019.9-2020.9 and 2019.9-2021.9. At the same time, the surrounding areas exhibited a positive and negative quadrant distribution. These observations indicate that the source region was likely in a stable locked state, with locking-in shear forces oriented in the NW and NE directions. From 2021.9 to 2022.8, the epicentral region showed negative density changes, indicating that the source region was in the expansion stage, approaching a near-seismic state. The three-dimensional density vertical slices reveal a southeastward migration of positive and negative densities near the epicenter and on the western of the Xianshuihe Fault Zone, indicating that the material is flowing out to the southeast. The observed local negative density changes at the epicenter along the Longmenshan Fault Zone are likely associated with the NE-oriented extensional stress shown by the seismic source mechanism. The above results can provide a basis for interpreting pre-earthquake gravity and density changes,thereby contributing to the advancement of earthquake precursor theory.展开更多
基金supported by the Henan Province Key R&D Project under Grant 241111210400the Henan Provincial Science and Technology Research Project under Grants 252102211047,252102211062,252102211055 and 232102210069+2 种基金the Jiangsu Provincial Scheme Double Initiative Plan JSS-CBS20230474,the XJTLU RDF-21-02-008the Science and Technology Innovation Project of Zhengzhou University of Light Industry under Grant 23XNKJTD0205the Higher Education Teaching Reform Research and Practice Project of Henan Province under Grant 2024SJGLX0126。
文摘Accurate and efficient detection of building changes in remote sensing imagery is crucial for urban planning,disaster emergency response,and resource management.However,existing methods face challenges such as spectral similarity between buildings and backgrounds,sensor variations,and insufficient computational efficiency.To address these challenges,this paper proposes a novel Multi-scale Efficient Wavelet-based Change Detection Network(MewCDNet),which integrates the advantages of Convolutional Neural Networks and Transformers,balances computational costs,and achieves high-performance building change detection.The network employs EfficientNet-B4 as the backbone for hierarchical feature extraction,integrates multi-level feature maps through a multi-scale fusion strategy,and incorporates two key modules:Cross-temporal Difference Detection(CTDD)and Cross-scale Wavelet Refinement(CSWR).CTDD adopts a dual-branch architecture that combines pixel-wise differencing with semanticaware Euclidean distance weighting to enhance the distinction between true changes and background noise.CSWR integrates Haar-based Discrete Wavelet Transform with multi-head cross-attention mechanisms,enabling cross-scale feature fusion while significantly improving edge localization and suppressing spurious changes.Extensive experiments on four benchmark datasets demonstrate MewCDNet’s superiority over comparison methods:achieving F1 scores of 91.54%on LEVIR,93.70%on WHUCD,and 64.96%on S2Looking for building change detection.Furthermore,MewCDNet exhibits optimal performance on the multi-class⋅SYSU dataset(F1:82.71%),highlighting its exceptional generalization capability.
基金supported by the funding Riset Unggulan Daerah 2022 of the Bureau of Development Planning and Research in Central Java Province(BAPPEDA Provinsi Jawa Tengah).
文摘Located downstream the Kupang Catchment in Indonesia,Pekalongan faces significant land subsidence issues,leading to severe coastal flooding.This study aimed to assess the impact of climate change on future flow regimes and hydrological extremes to inform long-term water resources management strategies for the Kupang Catchment.Utilizing precipitation and air temperature data from general circulation models in the Coupled Model Intercomparison Project 6(CMIP6)and employing bias correction techniques,the Soil and Water Assessment Tool(SWAT)hydrological model was employed to analyze climate-induced changes in hydrological fluxes,specifically streamflow.Results indicated a consistent increase in monthly streamflow during the wet season,with a substantial rise of 22.8%,alongside a slight decrease of 18.0%during the dry season.Moreover,both the frequency and severity of extremely low and high flows were projected to intensify by approximately 50%and 70%,respectively,for a 20-year return period,suggesting heightened flood and drought risks in the future.The observed declining trend in low flow,by up to 11%,indicated the potential for long-term groundwater depletion exacerbating the threat of land subsidence and coastal flooding,especially in areas with inadequate surface water management policies and infrastructure.
基金supported by the National Natural Science Foundation of China(No.82025030,No.72394404)the National Key Research and Development Program of China(No.2022YFC3702700)the National Research Program for Key Issues in Air Pollution Control of China(No.DQGG0401).
文摘As global greenhouse gases continue rising,the urgency of more ambitious action is clearer than ever before.China is the world’s biggest emitter of greenhouse gases and one of the countries affected most by climate change.The evidence about the impacts of climate change on the environment and human health may encourage China to take more decisive action to mitigate greenhouse gas emissions and adapt to climate impacts.
基金supported by the National Natural Science Foundation of China(No.52127816),the National Key Research and Development Program of China(No.2020YFA0715000)the National Natural Science and Hong Kong Research Grant Council Joint Research Funding Project of China(No.5181101182)the NSFC/RGC Joint Research Scheme sponsored by the Research Grants Council of Hong Kong and the National Natural Science Foundation of China(No.N_PolyU513/18).
文摘Latent heat thermal energy storage(TES)effectively reduces the mismatch between energy supply and demand of renewable energy sources by the utilization of phase change materials(PCMs).However,the low thermal conductivity and poor shape stability are the main drawbacks in realizing the large-scale application of PCMs.Promisingly,developing composite PCM(CPCM)based on porous supporting mate-rial provides a desirable solution to obtain performance-enhanced PCMs with improved effective thermal conductivity and shape stability.Among all the porous matrixes as supports for PCM,three-dimensional carbon-based porous supporting material has attracted considerable attention ascribing to its high ther-mal conductivity,desirable loading capacity of PCMs,and excellent chemical compatibility with various PCMs.Therefore,this work systemically reviews the CPCMs with three-dimensional carbon-based porous supporting materials.First,a concise rule for the fabrication of CPCMs is illustrated in detail.Next,the experimental and computational research of carbon nanotube-based support,graphene-based support,graphite-based support and amorphous carbon-based support are reviewed.Then,the applications of the shape-stabilized CPCMs including thermal management and thermal conversion are illustrated.Last but not least,the challenges and prospects of the CPCMs are discussed.To conclude,introducing carbon-based porous materials can solve the liquid leakage issue and essentially improve the thermal conductivity of PCMs.However,there is still a long way to further develop a desirable CPCM with higher latent heat capacity,higher thermal conductivity,and more excellent shape stability.
基金National Natural Science Foundation of China,No.41761003The Karst Science Research Center of Guizhou Province,No.U1812401。
文摘Terrestrial ecosystems heavily depend on vegetation,which responds to carbon dioxide(CO_(2))fertilization in hot and humid regions.The subtropical humid karst region is a hot and humid region;whether and to what extent CO_(2)fertilization affects vegetation changes in such regions remains unclear.In this study,we investigated the degree to which CO_(2)fertilization influences vegetation changes,along with their spatial and temporal differences,in the subtropical humid karst region using time-lag effect analysis,a random forest model,and multiple regression analysis.Results showed that CO_(2)fertilization plays an important role in vegetation changes,exhibiting clear spatial variations across different geomorphological zones,with its degree of influence ranging mainly between 11%and 25%.The highest contribution of CO_(2)fertilization was observed in the karst basin and non-karstic region,whereas the lowest contribution was found in the karst plateau region.Previous studies have primarily attributed vegetation changes in subtropical humid karst region to ecological engineering,leading to an overestimation of its contribution to these changes.The findings of this study enhance the understanding of the mechanism of vegetation changes in humid karst region and provide theoretical and practical insights for ecological and environmental protection in these regions.
基金supported by the Science and Technology Program of Fujian Province,China(No.2023R1014002)the National Natural Science Foundation of China(No.41471390).
文摘The toxicity of PM_(2.5)does not necessarily change synchronously with its mass concentration.In this study,the chemical composition(carbonaceous species,water-soluble ions,and metals)and oxidative potential(dithiothreitol assay,DTT)of PM_(2.5)were investigated in 2017/2018 and 2022 in Xiamen,China.The decrease rate of volume-normalized DTT(DTTv)(38%)was lower than that of PM_(2.5)(55%)between the two sampling periods.However,the mass-normalized DTT(DTTm)increased by 44%.Clear seasonal patterns with higher levels in winter were found for PM_(2.5),most chemical constituents and DTTv but not for DTTm.The large decrease in DTT activity(84%−92%)after the addition of EDTA suggested that watersoluble metals were the main contributors to DTT in Xiamen.The increased gap between the reconstructed and measured DTTv and the stronger correlations between the reconstructed/measured DTT ratio and carbonaceous species in 2022were observed.The decrease rates of the hazard index(32.5%)and lifetime cancer risk(9.1%)differed from those of PM_(2.5)and DTTv due to their different main contributors.The PMF-MLR model showed that the contributions(nmol/(min·m^(3)))of vehicle emission,coal+biomass burning,ship emission and secondary aerosol to DTTv in 2022 decreased by 63.0%,65.2%,66.5%,and 22.2%,respectively,compared to those in 2017/2018,which was consistent with the emission reduction of vehicle exhaust and coal consumption,the adoption of low-sulfur fuel oil used on board ships and the reduced production of WSOC.However,the contributions of dust+sea salt and industrial emission increased.
基金funded by the National Natural Science Foundation of China(32372546)Shenzhen Science and Technology Program(KQTD20180411143628272)+1 种基金the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences and STI 2030-Major Projects(2022ZD04021)the National Key Research and Development Program of China(2023YFD2200700)。
文摘Agricultural pests cause enormous losses in annual agricultural production.Understanding the evolutionary responses and adaptive capacity of agricultural pests under climate change is crucial for establishing sustainable and environmentally friendly agricultural pest management.In this study,we integrate climate modeling and landscape genomics to investigate the distributional dynamics of the cotton bollworm(Helicoverpa armigera)in the adaptation to local environments and resilience to future climate change.Notably,the predicted inhabitable areas with higher suitability for the cotton bollworm could be eight times larger in the coming decades.Climate change is one of the factors driving the dynamics of distribution and population differentiation of the cotton bollworm.Approximately 19,000 years ago,the cotton bollworm expanded from its ancestral African population,followed by gradual occupations of the European,Asian,Oceanian,and American continents.Furthermore,we identify seven subpopulations with high dispersal and adaptability which may have an increased risk of invasion potential.Additionally,a large number of candidate genes and SNPs linked to climatic adaptation were mapped.These findings could inform sustainable pest management strategies in the face of climate change,aiding future pest forecasting and management planning.
文摘BACKGROUND Atypical optic neuritis,consisting of neuromyelitis optica spectrum disorders(NMOSD)or myelin oligodendrocyte glycoprotein antibody disease(MOGAD),has a very similar presentation but different prognostic implications and longterm management strategies.Vascular and metabolic factors are being thought to play a role in such autoimmune neuro-inflammatory disorders,apart from the obvious immune mediated damage.With the advent of optical coherence tomography angiography(OCTA),it is easy to pick up on these subclinical macular microvascular and structural changes.AIM To study the macular microvascular and structural changes on OCTA in atypical optic neuritis.METHODS This observational cross-sectional study involved 8 NMOSD and 17 MOGAD patients,diagnosed serologically,as well as 10 healthy controls.Macular vascular density(MVD)and ganglion cell+inner plexiform layer thickness(GCIPL)were studied using OCTA.RESULTS There was a significant reduction in MVD in NMOSD and MOGAD affected as well as unaffected eyes when compared with healthy controls.NMOSD and MOGAD affected eyes had significant GCIPL thinning compared with healthy controls.NMOSD unaffected eyes did not show significant GCIPL thinning compared to healthy controls in contrast to MOGAD unaffected eyes.On comparing NMOSD with MOGAD,there was no significant difference in terms of MVD or GCIPL in the affected or unaffected eyes.CONCLUSION Although significant microvascular and structural changes are present on OCTA between atypical optic neuritis and normal patients,they could not help in differentiating between NMOSD and MOGAD cases.
文摘Gas-bearing shales have become a major source of future natural gas production worldwide.It has become increasingly urgent to develop a reliable prediction model and corresponding workflow for identifying shale gas sweet spots.The formation of gas-bearing shales is closely linked to relative sealevel changes,providing an important approach to predicting sweet spots in the Wufeng-Longmaxi shale in the southern Sichuan Basin,China.Three types of marine shale gas sweet spots are identified in the shale based on their formation stages combined with relative sea-level changes:early,middle,and late transgression types.This study develops a prediction model and workflow for identifying shale gas sweet spots by analyzing relative sea-level changes and facies sequences.Predicting shale gas sweet spots in an explored block using this model and workflow can provide a valuable guide for well design and hydraulic fracturing,significantly enhancing the efficiency of shale gas exploration and development.Notably,the new prediction model and workflow can be utilized for the rapid evaluation of the potential for shale gas development in new shale gas blocks or those with low exploratory maturity.
文摘We examine possible funding sources for constructing Climate Change Haven Communities on a global basis. Areas of the planet that have the potential to house persons migrating to “safe havens” in their own or other countries will require the rapid construction of communities capable of supporting them, their families, businesses and farms. However, different political-economic conditions are found across the areas which can serve as locations for these Climate Change Haven Communities. We develop funding and construction strategies for the United States (free-market capitalism), France and Spain (European Union supported economies), and Taiwan region (state-directed economy). The proposals for the Taiwan region should also be applicable to the rest of China.
基金funded by the Postdoctoral Research Startup Foundation of University of Jinan(Grant No.100389917).
文摘Climate change and anthropogenic activities have driven significant terrestrial water storage changes(TWSC)in the Three Rivers Source Region(TRSR),exerting profound impacts on freshwater availability across China and broader Asia.However,long-term TWSC characterization remains challenging due to limited observational data in this alpine region.Here,we integrate GRACE observations(2002-2020),ERA5-Land reanalysis,and GLDAS data to reconstruct TWSC using two methods:(1)the water balance method(PER)and(2)the component summation method(SS),applied to three input datasets(ERA5-Land,GLDAS,and their average,GLER).Comparative analysis reveals that the SS method applied to GL-ER yields the highest consistency with GRACE-derived TWSC.Using this optimal approach,we extend the analysis to 1951~2020,uncovering spatiotemporal TWSC patterns.Although annual TWSC trends appear negligible due to strong seasonality,we introduce the intra-year TWSC fluctuation(TWSCF)index to quantify cumulative variability.A significant(p<0.05)transition occurred in 1980,with TWSCF shifting from a declining trend(-0.39 mm/yr)to an increasing trend(0.56 mm/yr),primarily driven by soil moisture changes.However,Hurst exponent analysis suggests this upward trend may not persist.Drought and vegetation assessments indicate concurrent wetting and greening in the TRSR.TWSC correlates strongly with meteorological drought,acting as a reliable drought indicator while its linkage with vegetation dynamics suggests a potential contribution to greening.Our findings provide a robust framework for understanding long-term TWSC evolution and its hydrological-ecological interactions under climate change.
文摘BACKGROUND Dyslipidemia was strongly linked to stroke,however the relationship between dyslipidemia and its components and ischemic stroke remained unexplained.AIM To investigate the link between longitudinal changes in lipid profiles and dyslipidemia and ischemic stroke in a hypertensive population.METHODS Between 2013 and 2014,6094 hypertension individuals were included in this,and ischemic stroke cases were documented to the end of 2018.Longitudinal changes of lipid were stratified into four groups:(1)Normal was transformed into normal group;(2)Abnormal was transformed into normal group;(3)Normal was transformed into abnormal group;and(4)Abnormal was transformed into abnormal group.To examine the link between longitudinal changes in dyslipidemia along with its components and the risk of ischemic stroke,we utilized multivariate Cox proportional hazards models with hazard ratio(HR)and 95%CI.RESULTS The average age of the participants was 62.32 years±13.00 years,with 329 women making up 54.0%of the sample.Over the course of a mean follow-up of 4.8 years,143 ischemic strokes happened.When normal was transformed into normal group was used as a reference,after full adjustments,the HR for dyslipidemia and ischemic stroke among abnormal was transformed into normal group,normal was transformed into abnormal group and abnormal was transformed into abnormal Wei CC et al.Dyslipidemia changed and ischemic stroke WJCC https://www.wjgnet.com 2 February 6,2025 Volume 13 Issue 4 group were 1.089(95%CI:0.598-1.982;P=0.779),2.369(95%CI:1.424-3.941;P<0.001)and 1.448(95%CI:1.002-2.298;P=0.047)(P for trend was 0.233),respectively.CONCLUSION In individuals with hypertension,longitudinal shifts from normal to abnormal in dyslipidemia-particularly in total and low-density lipoprotein cholesterol-were significantly associated with the risk of ischemic stroke.
基金Funded by Scientific and Technological Innovation Project of Carbon Emission Peak and Carbon Neutrality of Jiangsu Province(No.BE2022028-4)。
文摘We adopted the solution impregnation route with aluminum dihydrogen phosphate solution as liquid medium for effective surface modification on graphite substrate.The mass ratio of graphite to Al(H_(2)PO_(4))_(3) changed from 0.5:1 to 4:1,and the impregnation time changed from 1 to 7 h.The typical composite phase change thermal storage materials doped with the as-treated graphite were fabricated using form-stable technique.To investigate the oxidation and anti-oxidation behavior of the impregnated graphite at high temperatures,the samples were put into a muffle furnace for a cyclic heat test.Based on SEM,EDS,DSC techniques,analyses on the impregnated technique suggested an optimized processing conditions of a 3 h impregnation time with the ratio of graphite:Al(H_(2)PO_(4))_(3) as 1:3 for graphite impregnation treatment.Further investigations on high-temperature phase change heat storage materials doped by the treated graphite suggested excellent oxidation resistance and thermal cycling performance.
文摘Oriented graphene aerogels have limited applica-tions because the flexibility of their graphene sheets and mi-crostructure give them a low skeleton strength,insufficient compression resilience,and poor flexibility.We report the preparation of novel aerogel materials with a much better per-formance.Using the driving force of graphene oxide(GO)self-assembly andπ-πinteractions,carbon nanotubes(CNTs)were attached to the GO sheets,and an oriented composite carbon skeleton was constructed using“hydro-plastic foam-ing”.The introduction of CNTs significantly increased the strength of the skeleton and gave the aerogel an excellent re-versible compressibility.The innovative use of cold pressing greatly improved the thermal conductivity and flexibility of the aerogel,providing new ideas for the development of high-performance aerogels.Tests show that the obtained graphene composite aerogel has a reversible compressive strain of over 90%and can withstand 500 compression cycles along the direc-tion of pore accumulation.It can endure more than 10000 bending cycles perpendicular to the direction of composite carbon layer stacking,and its in-plane thermal conductivity reaches 64.5 W·m^(-1)·K^(-1).When filled with phase change materials,the high porosity of the carbon skeleton enables the material to have a high phase change filling rate,and its phase change enthalpy is greater than 150 J/g.Thanks to the exceptional flexibility of the carbon skeleton,the macrostructure of phase change materials can be bent as needed to adapt to thermal management scenarios and conform to device shapes.This significantly enhances practical application compatibility,providing flexible support for temperature control and thermal management across diverse device forms.
文摘In Niger, farms have been facing negative effects of climate change for several decades. The objective of this work is to assess the vulnerability of farms in Tillabery department by proposing an adaptation approach. A five-step method and descriptive analysis were used on a sample of 250 farmers. The degree of damage caused by pests and crop diseases is significant, with respective proportions of 52.50% and 40.40%. It appears that the main climate risk factors for vulnerability are droughts, floods, soil degradation, and pest invasions. Additionally, the average level of exposure to agricultural operations is very high, with an index of 0.6. The sensitivity index remained constant in the range of 0.3 to 0.6 and is significant (reaching an index of 0.8). However, 61.2% of farms have a medium level of vulnerability and 33.3% have a high vulnerability to the effects of climate change. Nonetheless, a concerning trend regarding the vulnerability of farms has been observed. To assist policymakers and development actors in improving the vulnerability level of these production units, four phases of action are proposed: a diagnostic phase, evaluation, estimation of adaptation needs, implementation, and proper monitoring of actions.
文摘The department of Tillabéri is primarily affected by climatic phenomena, impacting crop yields, growing cycles, and consequently, the economic outcomes of agricultural operations. The objective of this study is to analyze these impacts of climate disruption on the economic performance of farms. The methodology adopted for this study combined documentary research with field surveys conducted on a sample of 250 randomly selected farmers. The analytical methods used mainly consisted of linear regression, profitability calculations, and linear programming. The findings indicate that all productions across different crops have experienced a decrease over the past 30 years. For instance, the production of millet, sorghum, and cowpea, which were respectively 812 kg/ha, 260 kg/ha, and 100 kg/ha between the last 30 and 20 years, has now dropped to 412 kg/ha, 106 kg/ha, and 46 kg/ha respectively. A negative and significant effect on agricultural net margin was observed due to variables such as flooding, drought, pest invasion in rice fields, and temperature changes. Smallholder farms show a relatively low margin (46%) to cover their fixed costs, which may indicate a risk if fixed expenses are high. Furthermore, the analysis results from linear programming reveal that farmers could achieve an additional net profit per hectare of 116,861 FCFA, 217201.5 FCFA, and 291988.2 FCFA respectively for small, medium, and large producers by managing variable costs and health-related expenses for households.
文摘Objective Primary liver cancer,predominantly hepatocellular carcinoma(HCC),is a significant global health issue,ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality.Accurate and early diagnosis of HCC is crucial for effective treatment,as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma(ICC)exhibit different prognoses and treatment responses.Traditional diagnostic methods,including liver biopsy and contrast-enhanced ultrasound(CEUS),face limitations in applicability and objectivity.The primary objective of this study was to develop an advanced,lightweighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images.The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions.Methods This retrospective study encompassed a total of 161 patients,comprising 131 diagnosed with HCC and 30 with non-HCC malignancies.To achieve accurate tumor detection,the YOLOX network was employed to identify the region of interest(ROI)on both B-mode ultrasound and CEUS images.A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images.These curves provided critical data for the subsequent analysis and classification process.To analyze the extracted brightness change curves and classify the malignancies,we developed and compared several models.These included one-dimensional convolutional neural networks(1D-ResNet,1D-ConvNeXt,and 1D-CNN),as well as traditional machine-learning methods such as support vector machine(SVM),ensemble learning(EL),k-nearest neighbor(KNN),and decision tree(DT).The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics:area under the receiver operating characteristic(AUC),accuracy(ACC),sensitivity(SE),and specificity(SP).Results The evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM,0.56 for ensemble learning,0.63 for KNN,and 0.72 for the decision tree.These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves.In contrast,the deep learning models demonstrated significantly higher AUCs,with 1D-ResNet achieving an AUC of 0.72,1D-ConvNeXt reaching 0.82,and 1D-CNN obtaining the highest AUC of 0.84.Moreover,under the five-fold cross-validation scheme,the 1D-CNN model outperformed other models in both accuracy and specificity.Specifically,it achieved accuracy improvements of 3.8%to 10.0%and specificity enhancements of 6.6%to 43.3%over competing approaches.The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification.Conclusion The 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies,surpassing both traditional machine-learning methods and other deep learning models.This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’diagnostic capabilities.By improving the accuracy and efficiency of clinical decision-making,this tool has the potential to positively impact patient care and outcomes.Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.
基金supported by the Kushlan Fund from the University of Miami Department of Biology.
文摘South Florida’s natural forest ecosystems,including pine rocklands and hardwood hammocks,are threatened by land use change and urbanization,invasive species,and climate change.It is critical to understand the responses of these ecosystems to anthropogenic disturbances to conserve the remnants of the USA natural subtropical forests.Using dendrochronology,long-term growth patterns were characterized in three dominant native tree species:Bursera simaruba,Swietenia mahagoni,and Pinus elliottii.Core samples were collected from>30 individuals of each species in hardwood hammocks(B.simaruba and S.mahagoni)and pine rocklands(P.elliottii)to examine growth patterns.Relationships between annual tree growth rates and climatic variables were assessed to address three questions:(1)What are the climatic drivers of growth in these three South Florida tree species?(2)Are their growth rates stable or changing through time?and(3)Are tree growth rates affected by urbanization?Standardized growth rates of the three species have changed through time,with small young trees showing accelerated growth through time,whereas larger,older trees showed declining growth rates.S.mahagoni and B.simaruba grew faster in urbanized parks than in more natural parks,whereas P.elliottii grew slower in urban parks.There were positive correlations between tree growth and the current year’s fall precipitation and no discernable effects of the current year’s monthly temperatures on growth rates of any of the species.These results suggest that the foundational tree species of the southern USA endangered pine rocklands and hardwood hammocks may be vulnerable to ongoing changes in precipitation and temperature as well as other environmental effects associated with urbanization.
基金the National Natural Science Foundation of China(Grant No.42374105,42204089,42174104)Scientific Research Fund of Institute of Seismology,China Earthquake Administration(Grant No.IS202326341,IS202336350).
文摘On September 5, 2022, an earthquake of magnitude M_(S)6.8 occurred in Luding County, Sichuan Province.This earthquake occurred at the key part of the southeast-clockwise extrusion of material on the eastern margin of the Qinghai Plateau, the Y-shaped confluence of the Xianshuihe, Longmenshan and Anninghe fault zones. In this study, the three-dimensional dynamic crustal density changes in the earthquake area are obtained by the typical gravity change data from 2019 to 2022 before the earthquake and gravity inversion by growing bodies. The results indicate that gravity changes presented an obvious fourquadrant and gradient belt distribution in the Luding area before the earthquake. The threedimensional density horizontal slices show that small density changes occurred at the epicenter in the mid-to-upper crust between 2019.9-2020.9 and 2019.9-2021.9. At the same time, the surrounding areas exhibited a positive and negative quadrant distribution. These observations indicate that the source region was likely in a stable locked state, with locking-in shear forces oriented in the NW and NE directions. From 2021.9 to 2022.8, the epicentral region showed negative density changes, indicating that the source region was in the expansion stage, approaching a near-seismic state. The three-dimensional density vertical slices reveal a southeastward migration of positive and negative densities near the epicenter and on the western of the Xianshuihe Fault Zone, indicating that the material is flowing out to the southeast. The observed local negative density changes at the epicenter along the Longmenshan Fault Zone are likely associated with the NE-oriented extensional stress shown by the seismic source mechanism. The above results can provide a basis for interpreting pre-earthquake gravity and density changes,thereby contributing to the advancement of earthquake precursor theory.
