Semantic Segmentation of Lumbar Vertebrae Using Meijering U-Net(MU-Net)on Spine Magnetic Resonance Images

Lower back pain is one of the most common medical problems in the world and it is experienced by a huge percentage of people everywhere.Due to its ability to produce a detailed view of the soft tissues,including the spinal cord,nerves,intervertebral discs,and vertebrae,Magnetic Resonance Imaging is thought to be the most effective method for imaging the spine.The semantic segmentation of vertebrae plays a major role in the diagnostic process of lumbar diseases.It is difficult to semantically partition the vertebrae in Magnetic Resonance Images from the surrounding variety of tissues,including muscles,ligaments,and intervertebral discs.U-Net is a powerful deep-learning architecture to handle the challenges of medical image analysis tasks and achieves high segmentation accuracy.This work proposes a modified U-Net architecture namely MU-Net,consisting of the Meijering convolutional layer that incorporates the Meijering filter to perform the semantic segmentation of lumbar vertebrae L1 to L5 and sacral vertebra S1.Pseudo-colour mask images were generated and used as ground truth for training the model.The work has been carried out on 1312 images expanded from T1-weighted mid-sagittal MRI images of 515 patients in the Lumbar Spine MRI Dataset publicly available from Mendeley Data.The proposed MU-Net model for the semantic segmentation of the lumbar vertebrae gives better performance with 98.79%of pixel accuracy(PA),98.66%of dice similarity coefficient(DSC),97.36%of Jaccard coefficient,and 92.55%mean Intersection over Union(mean IoU)metrics using the mentioned dataset.

An Efficient Local Radial Basis Function Method for Image Segmentation Based on the Chan-Vese Model

In this paper,we consider the Chan–Vese(C-V)model for image segmentation and obtain its numerical solution accurately and efficiently.For this purpose,we present a local radial basis function method based on a Gaussian kernel(GA-LRBF)for spatial discretization.Compared to the standard radial basis functionmethod,this approach consumes less CPU time and maintains good stability because it uses only a small subset of points in the whole computational domain.Additionally,since the Gaussian function has the property of dimensional separation,the GA-LRBF method is suitable for dealing with isotropic images.Finally,a numerical scheme that couples GA-LRBF with the fourth-order Runge–Kutta method is applied to the C-V model,and a comparison of some numerical results demonstrates that this scheme achieves much more reliable image segmentation.

Comparative analysis of recent hydrological models and an attempt to generate new combined products for monitoring terrestrial water storage change

Hydrological models are crucial for characterizing large-scale water quantity variations and correcting GNSS reference station vertical displacements.We evaluated the robustness of multiple models,such as the Global Land Data Assimilation System (GLDAS),the Famine Early Warning System Network Land Data Assimilation System (FLDAS),the National Centers for Environmental Prediction (NCEP),and the WaterGAP Global Hydrology Model (WGHM).Inter-model and outer comparisons with Global Positioning System (GPS) coordinate time series,satellite gravity field Mascon solutions,and Global Precipitation Climatology Centre (GPCC) guide our assessment.Results confirm WGHM's 26% greater effectiveness in correcting nonlinear variations in GPS height time series compared to NCEP.In the Amazon River Basin,a 5-month lag between FLDAS,GLDAS,and satellite gravity results is observed.In eastern Asia and Australia,NCEP's Terrestrial Water Storage Changes (TWSC)-derived surface displacements correlate differently with precipitation compared to other models.Three combined hydrological models (H-VCE,H-EWM,and H-CVM) utilizing Variance Component Estimation (VCE),Entropy Weight Method (EWM),and Coefficient of Variation Method (CVM) are formulated.Correcting nonlinear variations with combined models enhances global GPS height scatter by 15%-17%.Correlation with precipitation increases by 25%-30%,and with satellite gravity,rises from 0.2 to 0.8 at maximum.The combined model eliminates time lag in the Amazon Basin TWSC analysis,exhibiting a four times higher signal-to-noise ratio than single models.H-VCE demonstrates the highest accuracy.In summary,the combined hydrological model minimizes discrepancies among individual models,significantly improving accuracy for monitoring large-scale TWSC.

The Cloud Model for Climate Change

In 1995, the Intergovernmental Panel on Climate Change (IPCC) released a thermodynamic model based on the Greenhouse Effect, aiming to forecast global temperatures. This study delves into the intricacies of that model. Some interesting observations are revealed. The IPCC model equated average temperatures with average energy fluxes, which can cause significant errors. The model assumed that all energy fluxes remained constant, and the Earth emitted infrared radiation as if it were a blackbody. Neither of those conditions exists. The IPCC’s definition of Climate Change only includes events caused by human actions, excluding most causes. Satellite data aimed at the tops of clouds may have inferred a high Greenhouse Gas absorption flux. The model showed more energy coming from the atmosphere than absorbed from the sun, which may have caused a violation of the First and Second Laws of Thermodynamics. There were unexpectedly large gaps in the satellite data that aligned with various absorption bands of Greenhouse Gases, possibly caused by photon scattering associated with re-emissions. Based on science, we developed a cloud-based climate model that complied with the Radiation Laws and the First and Second Laws of Thermodynamics. The Cloud Model showed that 81.3% of the outgoing reflected and infrared radiation was applicable to the clouds and water vapor. In comparison, the involvement of CO2 was only 0.04%, making it too minuscule to measure reliably.

Hydrologic Response to Future Climate Change in the Dulong-Irra-waddy River Basin Based on Coupled Model Intercomparison Project 6

Within the context of the Belt and Road Initiative(BRI)and the China-Myanmar Economic Corridor(CMEC),the Dulong-Ir-rawaddy(Ayeyarwady)River,an international river among China,India and Myanmar,plays a significant role as both a valuable hydro-power resource and an essential ecological passageway.However,the water resources and security exhibit a high degree of vulnerabil-ity to climate change impacts.This research evaluates climate impacts on the hydrology of the Dulong-Irrawaddy River Basin(DIRB)by using a physical-based hydrologic model.We crafted future climate scenarios using the three latest global climate models(GCMs)from Coupled Model Intercomparison Project 6(CMIP6)under two shared socioeconomic pathways(SSP2-4.5 and SSP5-8.5)for the near(2025-2049),mid(2050-2074),and far future(2075-2099).The regional model using MIKE SHE based on historical hydrologic processes was developed to further project future streamflow,demonstrating reliable performance in streamflow simulations with a val-idation Nash-Sutcliffe Efficiency(NSE)of 0.72.Results showed that climate change projections showed increases in the annual precip-itation and potential evapotranspiration(PET),with precipitation increasing by 11.3%and 26.1%,and PET increasing by 3.2%and 4.9%,respectively,by the end of the century under SSP2-4.5 and SSP5-8.5.These changes are projected to result in increased annual streamflow at all stations,notably at the basin’s outlet(Pyay station)compared to the baseline period(with an increase of 16.1%and 37.0%at the end of the 21st century under SSP2-4.5 and SSP5-8.5,respectively).Seasonal analysis for Pyay station forecasts an in-crease in dry-season streamflow by 31.3%-48.9%and 22.5%-76.3%under SSP2-4.5 and SSP5-8.5,respectively,and an increase in wet-season streamflow by 5.8%-12.6%and 2.8%-33.3%,respectively.Moreover,the magnitude and frequency of flood events are pre-dicted to escalate,potentially impacting hydropower production and food security significantly.This research outlines the hydrological response to future climate change during the 21st century and offers a scientific basis for the water resource management strategies by decision-makers.

A Lane Change Model Considering the Stability of Cooperative Adaptive Cruise Control Platoon Fleet

In this article,lane change models for mixed traffic flow under cooperative adaptive cruise control(CACC)platoon formation are established.The analysis begins by examining the impact of lane changes on traffic flow stability.The influences of various factors such as lane change locations,timing,and the current traffic state on stability are discussed.In this analysis,it is assumed that the lane change location and the entry position in the adjacent lane have already been selected,without considering the specific intention behind the lane change.The speeds of the involved vehicles are adjusted based on an existing lane change model,and various conditions are analyzed for traffic flow disturbances,including duration,shock amplitude,and driving delays.Numerical calculations are provided to illustrate these effects.Additionally,traffic flow stability is factored into the lane change decision-making process.By incorporating disturbances to the fleet into the lane change income model,both a lane change intention model and a lane change execution model are constructed.These models are then compared with a model that does not account for stability,leading to the corresponding conclusions.

Analysis to the Driving Force Model and Driving Factor on the Utilized Changes of Cultivated Land in Gonghe County

Using gradually regression analysis to establish the driving force model of utilized change of cultivated land in Gonghe County, and using path analysis, correlation analysis, partial correlation analysis and system dynamics method to inspect the effect of driving changing on cultivated land change under different change situations. Driving factors, action mechanism and process of utilized change of cultivated land were analyzed from the county territory scale level. At last, some corresponding policies and measures were put forward.

EFFECTIVE IMAGE SEGMENTATION FRAMEWORK FOR GAUSSIAN MIXTURE MODEL INCORPORATING LOCAL INFORMATION

A new two-step framework is proposed for image segmentation. In the first step, the gray-value distribution of the given image is reshaped to have larger inter-class variance and less intra-class variance. In the sec- ond step, the discriminant-based methods or clustering-based methods are performed on the reformed distribution. It is focused on the typical clustering methods-Gaussian mixture model （GMM） and its variant to demonstrate the feasibility of the framework. Due to the independence of the first step in its second step, it can be integrated into the pixel-based and the histogram-based methods to improve their segmentation quality. The experiments on artificial and real images show that the framework can achieve effective and robust segmentation results.

Analysis to the Driving Force Model and Drives Factor on the Utilized Changes of Cultivated Land in Qinghai Lake Area

Using path analysis, correlation analysis, partial correlation analysis and system dynamics method to study the driving force of cultivated land in Qinghai Lake Area, and using gradually regression analysis to establish the driving force model of utilized change of cultivated land. Driving factors, action mechanism and process of utilized change of cultivated land were analyzed, and the differences during all factors were compared. The study provides some decision basis for sustainable utilization and management of land resources in Qinghai Lake Area.

Projected changes in extreme snowfall events over the Tibetan Plateau based on a set of RCM simulations

Extreme snowfall events over the Tibetan Plateau(TP)cause considerable damage to local society and natural ecosystems.In this study,the authors investigate the projected changes in such events over the TP and its surrounding areas based on an ensemble of a set of 21st century climate change projections using a regional climate model,RegCM4.The model is driven by five CMIP5 global climate models at a grid spacing of 25 km,under the RCP4.5 and RCP8.5 pathways.Four modified ETCCDI extreme indices-namely,SNOWTOT,S1mm,S10mm,and Sx5day-are employed to characterize the extreme snowfall events.RegCM4 generally reproduces the spatial distribution of the indices over the region,although with a tendency of overestimation.For the projected changes,a general decrease in SNOWTOT is found over most of the TP,with greater magnitude and better cross-simulation agreement over the eastern part.All the simulations project an overall decrease in S1mm,ranging from a 25%decrease in the west and to a 50%decrease in the east of the TP.Both S10mm and Sx5day are projected to decrease over the eastern part and increase over the central and western parts of the TP.Notably,S10mm shows a marked increase(more than double)with high cross-simulation agreement over the central TP.Significant increases in all four indices are found over the Tarim and Qaidam basins,and northwestern China north of the TP.The projected changes show topographic dependence over the TP in the latitudinal direction,and tend to decrease/increase in low-/high-altitude areas.

A study on the simulation of carbon and water fluxes of Dangxiong alpine meadow and its response to climate change

The alpine meadow ecosystem accounts for 27%of the total area of the Tibetan Plateau and is also one of the most important vegetation types.The Dangxiong alpine meadow ecosystem,located in the south-central part of the Tibetan Plateau,is a typical example.To understand the carbon and water fluxes,water use efficiency(WUE),and their responses to future climate change for the alpine meadow ecosystem in the Dangxiong area,two parameter estimation methods,the Model-independent Parameter Estimation(PEST)and the Dynamic Dimensions Search(DDS),were used to optimize the Biome-BGC model.Then,the gross primary productivity(GPP)and evapotranspiration(ET)were simulated.The results show that the DDS parameter calibration method has a better performance.The annual GPP and ET show an increasing trend,while the WUE shows a decreasing trend.Meanwhile,ET and GPP reach their peaks in July and August,respectively,and WUE shows a“dual-peak”pattern,reaching peaks in May and November.Furthermore,according to the simulation results for the next nearly 100 years,the ensemble average GPP and ET exhibit a significant increasing trend,and the growth rate under the SSP5–8.5 scenario is greater than that under the SSP2–4.5 scenario.WUE shows an increasing trend under the SSP2–4.5 scenario and a significant increasing trend under the SSP5–8.5 scenario.This study has important scientific significance for carbon and water cycle prediction and vegetation ecological protection on the Tibetan Plateau.

Analysis of piezoelectric semiconductor fibers under gradient temperature changes

Piezoelectric semiconductors(PSs)possess both semiconducting properties and piezoelectric coupling effects,making them optimal building blocks for semiconductor devices.PS fiber-like structures have wide applications in multi-functional semiconductor devices.In this paper,a one-dimensional(1D)theoretical model is established to describe the piezotronic responses of a PS fiber under gradient temperature changes.The theoretical model aims to explain the mechanism behind the resistance change caused by such gradient temperature changes.Numerical results demonstrate that a gradient temperature change significantly affects the physical fields within the PS fiber,and can induce changes in its surface resistance.It provides important theoretical guidance on the development of piezotronic devices that are sensitive to temperature effects.

Simulation of Effects of Land Use Change on Climate in China by a Regional Climate Model

Climate effects of land use change in China as simulated by a regional climate model (RegCM2) are investigated. The model is nested in one-way mode within a global coupled atmosphere-ocean model (CSIRO R21L9 AOGCM). Two multi-year simulations, one with current land use and the other with potential vegetation cover, are conducted. Statistically significant changes of precipitation, surface air temperature, and daily maximum and daily minimum temperature are analyzed based on the difference between the two simulations. The simulated effects of land use change over China include a decrease of mean annual precipitation over Northwest China, a region with a prevalence of arid and semi-arid areas; an increase of mean annual surface air temperature over some areas; and a decrease of temperature along coastal areas. Summer mean daily maximum temperature increases in many locations, while winter mean daily minimum temperature decreases in East China and increases in Northwest China. The upper soil moisture decreases significantly across China. The results indicate that the same land use change may cause different climate effects in different regions depending on the surrounding environment and climate characteristics.

The impacts of climate change on wheat yield in the Huang-Huai-Hai Plain of China using DSSAT-CERES-Wheat model under different climate scenarios

Climate change has been documented as a major threat to current agricultural strategies.Progress in understanding the impact of climate change on crop yield is essential for agricultural climate adaptation,especially for the Huang-Huai-Hai Plain(3H Plain)of China which is an area known to be vulnerable to global warming.In this study,the impacts of climate change on winter wheat(Triticum aestivum L.)yield between the baseline period(1981–2010)and two Representative Concentration Pathways(RCP8.5 and RCP4.5)were simulated for the short-term(2010–2039),the medium-term(2040–2069)and the long-term(2070–2099)in the 3H Plain,by considering the relative contributions of changes in temperature,solar radiation and precipitation using the DSSAT-CERES-Wheat model.Results indicated that the maximum and minimum temperatures(TMAX and TMIN),solar radiation(SRAD),and precipitation(PREP)during the winter wheat season increased under these two RCPs.Yield analysis found that wheat yield increased with the increase in SRAD,PREP and CO2 concentration,but decreased with an increase in temperature.Increasing precipitation contributes the most to the total impact,increasing wheat yield by 9.53,6.62 and 23.73%for the three terms of future climate under RCP4.5 scenario,and 11.74,16.38 and 27.78%for the three terms of future climate under RCP8.5 scenario.However,as increases in temperature bring higher evapotranspiration,which further aggravated water deficits,the supposed negative effect of increasing thermal resources decreased wheat yield by 1.92,4.08 and 5.24%for the three terms of future climate under RCP4.5 scenario,and 3.64,5.87 and 5.81%for the three terms of future climate under RCP8.5 scenario with clearly larger decreases in RCP8.5.Counterintuitively,the impacts in southern sub-regions were positive,but they were all negative in the remaining sub-regions.Our analysis demonstrated that in the 3H Plain,which is a part of the mid-high latitude region,the effects of increasing thermal resources were counteracted by the aggravated water deficits caused by the increase in temperature.

Modelling Hydrological Consequences of Climate Change—Progress and Challenges

The simulation of hydrological consequences of climate change has received increasing attention from the hydrology and land-surface modelling communities. There have been many studies of climate-change effects on hydrology and water resources which usually consist of three steps： （1） use of general circulation models （GCMs） to provide future global climate scenarios under the effect of increasing greenhouse gases, （2） use of downscaling techniques （both nested regional climate models, RCMs, and statistical methods） for ＂downscaling＂ the GCM output to the scales compatible with hydrological models, and （3） use of hydrologic models to simulate the effects of climate change on hydrological regimes at various scales. Great progress has been achieved in all three steps during the past few years, however, large uncertainties still exist in every stage of such study. This paper first reviews the present achievements in this field and then discusses the challenges for future studies of the hydrological impacts of climate change.

Using ORYZA2000 to model cold rice yield response to climate change in the Heilongjiang province, China

Rice(Oryza sativa L.) is one of the most important staple crops in China. Increasing atmospheric greenhouse gas concentrations and associated climate change may greatly affect rice production. We assessed the potential impacts of climate change on cold rice production in the Heilongjiang province, one of China's most important rice production regions. Data for a baseline period(1961–1990) and the period 2010–2050 in A2 and B2 scenarios were used as input to drive the rice model ORYZA2000 with and without accounting for the effects of increasing atmospheric CO2 concentration. The results indicate that mean,maximum, and minimum temperature during the rice growing season, in the future period considered, would increase by 1.8 °C under the A2 scenario and by 2.2 °C under the B2 scenario compared with those in the baseline. The rate of change in average maximum and minimum temperatures would increase by 0.6 °C per 10-year period under the A2 scenario and by 0.4 °C per 10-year period under the B2 scenario. Precipitation would increase slightly in the rice growing season over the next 40 years. The rice growing season would be shortened and the yield would increase in most areas in the Heilongjiang province. Without accounting for CO2 effect, the rice growing season in the period 2010–2050 would be shortened by 4.7 and 5.8 days,and rice yields would increase by 11.9% and 7.9%, under the A2 and B2 scenarios, respectively.Areas with simulated rice yield increases greater than 30.0% were in the Xiaoxing'an Mountain region. The simulation indicated a decrease in yield of less than 15% in the southwestern Songnen Plain. The rate of change in simulated rice yield was 5.0% and 2.5% per 10 years under the A2 and B2 scenarios, respectively. When CO2 effect was accounted for, rice yield increased by 44.5% and 31.3% under the A2 and B2 scenarios, respectively. The areas of increasing yield were sharply expanded. The area of decreasing yield in the western region of Songnen Plains disappeared when increasing CO2 concentration was considered. The stability of rice yield would increase from 2010 to 2050. Overall, the simulation indicates that rice production will be affected positively by climate change in the next 40 years in the Heilongjiang province, China.

Dynamic changes of ocular biometric parameters:a modified form-deprivation myopia model of young guinea pigs

AIM: To evaluate the dynamic ocular biometric changes of a modified form-deprivation myopia model in young guinea pigs. METHODS: The animals were randomly assigned to two groups: the monocularly deprived facemask group (MDF, with all the right eyes covered, n=24) and the normal control group(free of facemask, n=24). Each group was then equally divided into four subgroups which were followed up for 2, 4, 6 and 8 weeks, respectively. Parameters measured from every eye included refraction, corneal curvature, axial length and the dry weight of sclera at the posterior pole. RESULTS: All the facemasks remained in place during the follow-up. The covered eyes developed myopia with the vitreous chamber lengthening and the dry weight of posterior sclera reduced at each time point compared with the contralateral uncovered (P<0.05 at all time points). The changes had a linear correlation with the deprivation time (P<0.05). There were no significant differences in all the parameters between the uncovered eyes of MDF group and the normal control group (P>0.05 at all time points). CONCLUSION: Monocular form deprivation with the facemask is highly effective and non-invasive in inducing axial myopia in guinea pigs. The axial myopia is mainly caused by the increased vitreous chamber length and the weakened posterior sclera rigidity. The form-deprivation eye didn't interfere with the natural development of the contralateral eye.

Shoreline Change Modeling on Emergency Beach Nourishment Project on West Beach of Beidaihe,China

By use of a shorehne-change numerical model （GENESIS） based on one-line theory, a preliminary modeling study on shoreline changes caused by a beach nourishment project in Beidaihe, China, is presented in this paper. Firstly, the GENESIS model is verified and model sensitivity to the major parameter changes is discussed by simulating a hydraulic model test. The beach nourishment project, after that the shoreline change is kept being monitored, is a small-scale emergency one carried out to use two bathing places on the west beach in the summer, 2008. In this paper the shoreline changes caused by the beach nourishment project are modeled by the GENESIS model, and the computed results fit well with the measured shorelines. With the same model and parameters, a long-term performance of the project is predicted, and the result shows that the bathing places only can be suitable for bathing in 2 to 3 years without subsequence nourishment project. Therefore, it is proposed to nourish the beaches in time to keep the service life of the beach in recent years and carry out the beach nourishment project for the whole west beach as soon as possible.

Assessment of wetland fragmentation in the middle reaches of the Heihe River by the type change tracker model

The quantitative research of wetland landscape fragmentation in the middle reaches of the Heihe River is important for the wetland and oasis sustainable development in the Hexi Corridor. Based on the data of remote sensing and GIS, we constructed the type change tracker model with sliding window technique and spatially mor- phological rule. The suitable scale and optimum scale of the fragmentation model of wetland landscape in the middle reaches of the Heihe River were determined by the area frequency statistics method, Chi-square distribution normal- ized scale variance, fractal dimension and diversity index. By integrating type change tracker model and the optimum scale with GIS spatial analysis, the spatial distribution characteristics of wetland landscape fragmentation in different periods and the related spatial-temporal change process were clarified. The results showed that （1） the type change tracker model, which analyzes the spatial pattern of wetland fragmentation on the pixel level, is better than the tradi- tional wetland fragmentation analysis on the landscape and patch levels; （2） The suitable scale for the wetland frag- mentation ranged from 150 rex150 m to 450 mx450 m and the optimum scale was 250 mx250 m in the middle reaches of the Heihe River; and （3） In the past 35 years, the total wetland area decreased by 23.2% and the frag- mentatJon of wetland markedly increased in the middle reaches of the Heihe River. The areas of core wetlands re- duced by 12.8% and the areas of perforated, edge and patch wetlands increased by 0.8%, 3.1% and 8.9%, respec- tively. The process of wetland fragmentation in the research region showed the order of core wetland, perforated or edge wetland, patch wetland or non-wetland. The results of this study would provide a reference for the protection, utilization and restoration of limited wetland resources and for the sustainable development of the regional eco-environment in the Heihe River Basin.

Multi-resolution image segmentation based on Gaussian mixture model

Mixture model based image segmentation method, which assumes that image pixels are independent and do not consider the position relationship between pixels, is not robust to noise and usually leads to misclassification. A new segmentation method, called multi-resolution Ganssian mixture model method, is proposed. First, an image pyramid is constructed and son-father link relationship is built between each level of pyramid. Then the mixture model segmentation method is applied to the top level. The segmentation result on the top level is passed top-down to the bottom level according to the son-father link relationship between levels. The proposed method considers not only local but also global information of image, it overcomes the effect of noise and can obtain better segmentation result. Experimental result demonstrates its effectiveness.