Effect of astigmatism and spherical equivalent correction on contrast sensitivity

AIM:To investigate the effect of astigmatism and spherical equivalent(SE)correction on contrast sensitivity(CS).METHODS:In this cross-sectional study,103 visually normal subjects aged 18 to 36y with bilateral regular astigmatism in range of 1.00 diopter cylinder(DC)to 4.00 DC and normal best-corrected visual acuity(20/20)were recruited.Binocular CS was assessed by linear sine-wave gratings at 1.5,3,6,12,and 18 cycles per degree(cpd),before correction of astigmatism,after full correction of astigmatism by cylindrical spectacle lenses,and after SE of refractive error.The repeated measures ANOVA and Bonferroni test were used to compare the effects of astigmatism correction on logCS.RESULTS:Totally 39 patients were male and 64 patients were female with the mean age of 28.25±5.38y.The average degree of astigmatism in right and left eye was 2.03±0.83 and 2.10±0.78,respectively.Increases in uncorrected astigmatic power correlated with decreases in the logCS,especially at high spatial frequencies.A statistically significant difference in logCS was found between these three cases:before correction of astigmatism,after SE of refractive error,and after full correction of astigmatism by cylindrical spectacle lenses at all frequencies(P<0.001),except at 18 cpd.At 18 cpd,there was no statistically significant difference between logCS before and after SE of refractive error(P=1.0).Also,there was no statistically significant difference in mean CS between with-the-rule(WTR)and against-the-rule(ATR)astigmatism,before correction of astigmatism,after correction of astigmatism with cylindrical lenses,and after SE of refractive error.CONCLUSION:Binocular astigmatism defocus decreases CS depending on the degree of astigmatism power;correction of this will improve patent’s quality of vision.Although high astigmatism refractive error(more than 2.00 DC)that is fully corrected by cylindrical spectacle lenses doesn’t increase the CS to the maximum value,especially at higher spatial frequencies(12 and 18).Also SE refractive error effects on improving CS in low astigmatism power(less than 2.00 DC),especially at lower spatial frequencies.

近红外无创血糖浓度的Label Sensitivity算法和支持向量机回归

近红外光谱分析技术在生物医学工程领域具有广阔应用前景。无创且持续性地测量能实时监控人体血糖水平,给糖尿病患者带来极大便利性、提高生存质量、降低糖尿病并发症发生率具有很大的社会效益。无创血糖监测的想法提出较早,但仍然存在预测精度低、预测值与标签值相关性不高等难点,至今没有达到临床要求。近年来,光谱检测技术发展迅猛且机器学习技术在智能信息处理方面具有明显优势,两者结合可以有效提高人体无创血糖医学监测模型的精度和普适性。提出了一种标签敏感度算法(LS),并结合支持向量机方法建立了人体血糖含量预测模型。使用近红外光谱仪采集了4名志愿者食指处动态血液光谱数据(每名志愿者28组数据),并使用多元散射矫正(MSC)方法消除了部分光散射的影响。考虑血糖对不同波长光的吸收有差异,提出了基于血糖浓度标签差的特征波长挑选方法,并构建了标签敏感度支持向量机(LSSVR)预测模型。设计实验,对比该模型与偏最小二乘回归(PLSR)和区分度支持向量机(FSSVR)算法。结果表明,LS算法的最佳特征波长数为32,经特征波长选择后的LSSVR表现最佳,其均方误差降低至0.02 mmol·L^(-1),明显优于全谱段PLSR模型,血糖浓度的预测值与标签值的相关系数提升至99.8%,预测值全部位于可容许误差的克拉克网格A区内。LSSVR模型的优异表现为早日实现血糖的无创监测提供了新思路。

Attribution of Biases of Interhemispheric Temperature Contrast in CMIP6 Models

One of the basic characteristics of Earth's modern climate is that the Northern Hemisphere(NH) is climatologically warmer than the Southern Hemisphere(SH). Here, model performances of this basic state are examined using simulation results from 26 CMIP6 models. Results show that the CMIP6 models underestimate the contrast in interhemispheric surface temperatures on average(0.8 K for CMIP6 mean versus 1.4 K for reanalysis data mean), and that there is a large intermodel spread, ranging from -0.7 K to 2.3 K. A box model energy budget analysis shows that the contrast in interhemispheric shortwave absorption at the top of the atmosphere, the contrast in interhemispheric greenhouse trapping, and the crossequatorial northward ocean heat transport, are all underestimated in the multimodel mean. By examining the intermodel spread, we find intermodel biases can be tracked back to biases in midlatitude shortwave cloud forcing in AGCMs. Models with a weaker interhemispheric temperature contrast underestimate the shortwave cloud reflection in the SH but overestimate the shortwave cloud reflection in the NH, which are respectively due to underestimation of the cloud fraction over the SH extratropical ocean and overestimation of the cloud liquid water content over the NH extratropical continents.Models that underestimate the interhemispheric temperature contrast exhibit larger double ITCZ biases, characterized by excessive precipitation in the SH tropics. Although this intermodel spread does not account for the multimodel ensemble mean biases, it highlights that improving cloud simulation in AGCMs is essential for simulating the climate realistically in coupled models.

Identification, pathogenicity, and fungicide sensitivity of Eutiarosporella dactylidis associated with leaf blight on maize in China

Maize(Zea mays L.) is an economically vital grain crop that is cultivated worldwide. In 2011, a maize foliar disease was detected in Lingtai and Lintao counties in Gansu Province, China. The characteristic signs and symptoms of this disease include irregular chlorotic lesions on the tips and edges of infected leaves and black punctate fruiting bodies in dead leaf tissues. Given favourable environmental conditions, this disease spread to areas surrounding Gansu. In this study, infected leaves were collected from Gansu and Ningxia Hui Autonomous Region between 2018and 2020 to identify the disease-causing pathogen. Based on morphological features, pathogenicity tests, and multilocus phylogenetic analysis involving internal transcribed spacer(ITS), 18S small subunit rDNA(SSU), 28S large subunit rDNA(LSU), translation elongation factor 1-alpha(TEF), and β-tubulin(TUB) sequences, Eutiarosporella dactylidis was identified as the causative pathogen of this newly discovered leaf blight. Furthermore, an in vitro bioassay was conducted on representative strains using six fungicides, and both fludioxonil and carbendazim were found to significantly inhibit the mycelial growth of E. dactylidis. The results of this study provide a reference for the detection and management of Eutiarosporella leaf blight.

Future changes in precipitation and water availability over the Tibetan Plateau projected by CMIP6 models constrained by climate sensitivity

Precipitation projections over the Tibetan Plateau(TP)show diversity among existing studies,partly due to model uncertainty.How to develop a reliable projection remains inconclusive.Here,based on the IPCC AR6–assessed likely range of equilibrium climate sensitivity(ECS)and the climatological precipitation performance,the authors constrain the CMIP6(phase 6 of the Coupled Model Intercomparison Project)model projection of summer precipitation and water availability over the TP.The best estimates of precipitation changes are 0.24,0.25,and 0.45 mm d^(−1)(5.9%,6.1%,and 11.2%)under the Shared Socioeconomic Pathway(SSP)scenarios of SSP1–2.6,SSP2–4.5,and SSP5–8.5 from 2050–2099 relative to 1965–2014,respectively.The corresponding constrained projections of water availability measured by precipitation minus evaporation(P–E)are 0.10,0.09,and 0.22 mm d^(−1)(5.7%,4.9%,and 13.2%),respectively.The increase of precipitation and P–E projected by the high-ECS models,whose ECS values are higher than the upper limit of the likely range,are about 1.7 times larger than those estimated by constrained projections.Spatially,there is a larger increase in precipitation and P–E over the eastern TP,while the western part shows a relatively weak difference in precipitation and a drier trend in P–E.The wetter TP projected by the high-ECS models resulted from both an approximately 1.2–1.4 times stronger hydrological sensitivity and additional warming of 0.6℃–1.2℃ under all three scenarios during 2050–2099.This study emphasizes that selecting climate models with climate sensitivity within the likely range is crucial to reducing the uncertainty in the projection of TP precipitation and water availability changes.

Navigating nephrotoxic waters:A comprehensive overview of contrast-induced acute kidney injury prevention

Contrast-induced acute kidney injury(CI-AKI)is the third leading cause of acute kidney injury deriving from the intravascular administration of contrast media in diagnostic and therapeutic procedures and leading to longer in-hospital stay and increased short and long-term mortality.Its pathophysiology,although not well-established,revolves around medullary hypoxia paired with the direct toxicity of the substance to the kidney.Critically ill patients,as well as those with pre-existing renal disease and cardiovascular comorbidities,are more susceptible to CI-AKI.Despite the continuous research in the field of CI-AKI prevention,clinical practice is based mostly on periprocedural hydration.In this review,all the investigated methods of prevention are presented,with an emphasis on the latest evidence regarding the potential of RenalGuard and contrast removal systems for CI-AKI prevention in high-risk individuals.

Efficient slope reliability and sensitivity analysis using quantile-based first-order second-moment method

This paper introduces a novel approach for parameter sensitivity evaluation and efficient slope reliability analysis based on quantile-based first-order second-moment method(QFOSM).The core principles of the QFOSM are elucidated geometrically from the perspective of expanding ellipsoids.Based on this geometric interpretation,the QFOSM is further extended to estimate sensitivity indices and assess the significance of various uncertain parameters involved in the slope system.The proposed method has the advantage of computational simplicity,akin to the conventional first-order second-moment method(FOSM),while providing estimation accuracy close to that of the first-order reliability method(FORM).Its performance is demonstrated with a numerical example and three slope examples.The results show that the proposed method can efficiently estimate the slope reliability and simultaneously evaluate the sensitivity of the uncertain parameters.The proposed method does not involve complex optimization or iteration required by the FORM.It can provide a valuable complement to the existing approximate reliability analysis methods,offering rapid sensitivity evaluation and slope reliability analysis.

MEAN SENSITIVITY AND BANACH MEAN SENSITIVITY FOR LINEAR OPERATORS

Let(X,T)be a linear dynamical system,where X is a Banach space and T:X→X is a bounded linear operator.This paper obtains that(X,T)is sensitive(Li-Yorke sensitive,mean sensitive,syndetically mean sensitive,respectively)if and only if(X,T)is Banach mean sensitive(Banach mean Li-Yorke sensitive,thickly multi-mean sensitive,thickly syndetically mean sensitive,respectively).Several examples are provided to distinguish between different notions of mean sensitivity,syndetic mean sensitivi`ty and mean Li-Yorke sensitivity.

Characterizing permeability-porosity relationships of porous rocks using a stress sensitivity model in consideration of elastic-structural deformation and tortuosity sensitivity

Clarifying the relationship between stress sensitivities of permeability and porosity is of great significance in guiding underground resource mining.More and more studies focus on how to construct stress sensitivity models to describe the relationship and obtain a comprehensive stress sensitivity of porous rock.However,the limitations of elastic deformation calculation and incompleteness of considered tortuosity sensitivity lead to the fact that the existing stress sensitivity models are still unsatisfactory in terms of accuracy and generalization.Therefore,a more accurate and generic stress sensitivity model considering elastic-structural deformation of capillary cross-section and tortuosity sensitivity is proposed in this paper.The elastic deformation is derived from the fractal scaling model and Hooke's law.Considering the effects of elastic-structural deformation on tortuosity sensitivity,an empirical formula is proposed,and the conditions for its applicability are clarified.The predictive performance of the proposed model for the permeability-porosity relationships is validated in several sets of publicly available experimental data.These experimental data are from different rocks under different pressure cycles.The mean and standard deviation of relative errors of predicted stress sensitivity with respect to experimental data are 2.63%and 1.91%.Compared with other models,the proposed model has higher accuracy and better predictive generalization performance.It is also found that the porosity sensitivity exponent a,which can describe permeability-porosity relationships,is 2 when only elastic deformation is considered.a decreases from 2 when structural deformation is also considered.In addition,a may be greater than 3 due to the increase in tortuosity sensitivity when tortuosity sensitivity is considered even if the rock is not fractured.

Signal intensity changes of dentate nucleus on plain MR T1WI innasopharyngeal carcinoma patients after radiotherapy andmultiple injections of gadolinium-base contrast agent

Objective To observe changes of plain MR T1WI signal intensity of dentate nucleus in nasopharyngeal carcinoma patients after radiotherapy and multiple times of intravenous injection of gadolinium-based contrast agent(GBCA).Methods Fifty patients with pathologically confirmed nasopharyngeal carcinoma and received intensity-modulated radiotherapy were retrospectively enrolled as the nasopharyngeal carcinoma group,and 50 patients with other malignant tumors and without history of brain radiotherapy were retrospectively enrolled as the control group.All patients received yearly GBCA enhanced MR examinations for the nasopharynx or the head.T1WI signal intensities of the dentate nucleus and the pons on same plane were measured based on images in the year of confirmed diagnosis(recorded as the first year)and in the second to the fifth years.T1WI signal intensity ratio of year i(ranging from 1 to 5)was calculated with values of dentate nucleus divided by values of the pons(ΔSI i),while the percentage of relative changes of year j(ranging from 2 to 5)was calculated withΔSI j compared toΔSI 1(Rchange j).The values of these two parameters were compared,and the correlation ofΔSI and GBCA injection year-time was evaluated within each group.Results No significant difference of gender,age norΔSI 1 was found between groups(all P>0.05).The second to the fifth yearΔSI and Rchange in nasopharyngeal carcinoma group were all higher than those in control group(all P<0.05).Within both groups,ΔSI was positively correlated with GBCA injection year-time(both P<0.05).Conclusion Patients with nasopharyngeal carcinoma who underwent radiotherapy and multiple times of intravenous injection of GBCA tended to be found with gradually worsening GBCA deposition in dentate nucleus,for which radiotherapy might be a risk factor.

Recommendation Method for Contrastive Enhancement of Neighborhood Information

Knowledge graph can assist in improving recommendation performance and is widely applied in various person-alized recommendation domains.However,existing knowledge-aware recommendation methods face challenges such as weak user-item interaction supervisory signals and noise in the knowledge graph.To tackle these issues,this paper proposes a neighbor information contrast-enhanced recommendation method by adding subtle noise to construct contrast views and employing contrastive learning to strengthen supervisory signals and reduce knowledge noise.Specifically,first,this paper adopts heterogeneous propagation and knowledge-aware attention networks to obtain multi-order neighbor embedding of users and items,mining the high-order neighbor informa-tion of users and items.Next,in the neighbor information,this paper introduces weak noise following a uniform distribution to construct neighbor contrast views,effectively reducing the time overhead of view construction.This paper then performs contrastive learning between neighbor views to promote the uniformity of view information,adjusting the neighbor structure,and achieving the goal of reducing the knowledge noise in the knowledge graph.Finally,this paper introduces multi-task learning to mitigate the problem of weak supervisory signals.To validate the effectiveness of our method,experiments are conducted on theMovieLens-1M,MovieLens-20M,Book-Crossing,and Last-FM datasets.The results showthat compared to the best baselines,our method shows significant improvements in AUC and F1.

A Rapid Adaptation Approach for Dynamic Air‑Writing Recognition Using Wearable Wristbands with Self‑Supervised Contrastive Learning

Wearable wristband systems leverage deep learning to revolutionize hand gesture recognition in daily activities.Unlike existing approaches that often focus on static gestures and require extensive labeled data,the proposed wearable wristband with selfsupervised contrastive learning excels at dynamic motion tracking and adapts rapidly across multiple scenarios.It features a four-channel sensing array composed of an ionic hydrogel with hierarchical microcone structures and ultrathin flexible electrodes,resulting in high-sensitivity capacitance output.Through wireless transmission from a Wi-Fi module,the proposed algorithm learns latent features from the unlabeled signals of random wrist movements.Remarkably,only few-shot labeled data are sufficient for fine-tuning the model,enabling rapid adaptation to various tasks.The system achieves a high accuracy of 94.9%in different scenarios,including the prediction of eight-direction commands,and air-writing of all numbers and letters.The proposed method facilitates smooth transitions between multiple tasks without the need for modifying the structure or undergoing extensive task-specific training.Its utility has been further extended to enhance human–machine interaction over digital platforms,such as game controls,calculators,and three-language login systems,offering users a natural and intuitive way of communication.

High-Precision Flow Numerical Simulation and Productivity Evaluation of Shale Oil Considering Stress Sensitivity

Continental shale oil reservoirs,characterized by numerous bedding planes and micro-nano scale pores,feature significantly higher stress sensitivity compared to other types of reservoirs.However,research on suitable stress sensitivity characterization models is still limited.In this study,three commonly used stress sensitivity models for shale oil reservoirs were considered,and experiments on representative core samples were conducted.By fitting and comparing the data,the“exponential model”was identified as a characterization model that accurately represents stress sensitivity in continental shale oil reservoirs.To validate the accuracy of the model,a two-phase seepage mathematical model for shale oil reservoirs coupled with the exponential model was introduced.The model was discretely solved using the finite volume method,and its accuracy was verified through the commercial simulator CMG.The study evaluated the productivity of a typical horizontal well under different engineering,geological,and fracture conditions.The results indicate that considering stress sensitivity leads to a 13.57%reduction in production for the same matrix permeability.Additionally,as the fracture half-length and the number of fractures increase,and the bottomhole flowing pressure decreases,the reservoir stress sensitivity becomes higher.

Sensitivity and resistance risk analysis of Didymella bryoniae populations to fluopyram

Fluopyram is an succinate dehydrogenase inhibitors(SDHI)fungicide that has been registered in China to control gummy stem blight(GSB)in watermelons for many years.However,whether the field pathogens of GSB are still sensitive to fluopyram or not is unknown.Therefore,we collected 69 Didymella bryoniae isolates from the fields that usually use fluopyram to control GSB to determine the sensitivity change.The EC_(50)(50%inhibition effect)values of fluopyram against D.bryoniae ranged from 0.0691 to 0.3503μg mL^(–1) and the variation factor was 5.07.The mean EC_(50) value was(0.1579±0.0669)μg mL^(–1) and the curve of sensitivity was unimodal.No resistant strains were found in the isolates,which means that the pathogens were still sensitive to fluopyram.The minimal inhibition concentration(MIC)of fluopyram against D.bryoniae was 3μg mL^(–1).Four low-resistant mutants and two medium-resistant mutants were obtained using fungicide taming and the resistance of mutants could be inherited stably.The growth rate of mutants decreased significantly compared with that of wild-type strains while the biomass of most mutants was similar to that of wild-type strains.The sensitivity of most resistant mutants to various stresses was increased compared with that of wild-type strains.The virulence of mutants receded except for low-resistant mutant XN51FR-1,which had the same lesion area as XN51 on the watermelon leaves.The results indicated that the fitness of resistant mutants was decreased compared with that of wild-type strains.The cross-resistance assay indicated that fluopyram-resistant mutants were positive cross-resistant to all six SDHI fungicides in this test but were still sensitive to fluazinam and tebuconazole.So the resistance risk of D.bryoniae to fluopyram was moderate.In addition,we found that the SdhB gene of low-resistant mutant XN30FR-1 had three new point mutations at positions K258N,A259P,and H277N.Medium-resistant mutant XN52FR-1 showed a mutation at position H277N and other mutants did not have any point mutation.

Optical design of a novel near-infrared phase contrast imaging(NI-PCI)diagnostic on the HL-2A tokamak

The optical design of near-infrared phase contrast imaging(NI-PCI)diagnosis on HL-2A is introduced in this paper.This scheme benefits from the great progress of near-infrared laser technology and is a broadening of traditional phase contrast technology.This diagnostic can work as a keen tool to measure plasma wavenumber spectra by inferring string-integrated plasma density fluctuations.Design of both the front optical path which is the path before the laser transmitting into the tokamak plasma and the rear optics which is the path after the laser passing through the plasma is detailed.The 1550 nm laser is chosen as the probe beam and highprecision optical components are designed to fit the laser beam,in which a phase plate with a 194-nm-deep silver groove is the key.Compared with the conventional 10.6μm laser-based PCI system on HL-2A,NI-PCI significantly overcomes the unwanted phase scintillation effect and promotes the measurement capability of high-wavenumber turbulence with an increased maximal measurable wavenumber from 15 cm^(-1)to 32.6 cm^(-1).

An efficient data-driven global sensitivity analysis method of shale gas production through convolutional neural network

The shale gas development process is complex in terms of its flow mechanisms and the accuracy of the production forecasting is influenced by geological parameters and engineering parameters.Therefore,to quantitatively evaluate the relative importance of model parameters on the production forecasting performance,sensitivity analysis of parameters is required.The parameters are ranked according to the sensitivity coefficients for the subsequent optimization scheme design.A data-driven global sensitivity analysis(GSA)method using convolutional neural networks(CNN)is proposed to identify the influencing parameters in shale gas production.The CNN is trained on a large dataset,validated against numerical simulations,and utilized as a surrogate model for efficient sensitivity analysis.Our approach integrates CNN with the Sobol'global sensitivity analysis method,presenting three key scenarios for sensitivity analysis:analysis of the production stage as a whole,analysis by fixed time intervals,and analysis by declining rate.The findings underscore the predominant influence of reservoir thickness and well length on shale gas production.Furthermore,the temporal sensitivity analysis reveals the dynamic shifts in parameter importance across the distinct production stages.

Near-Infrared Fluorescence Imaging Contrast Agents for Clinical Research: Limitations and Alternatives

Introduction: Near-infrared fluorescence imaging is a technique that will establish itself in the short term at the international level because it is recognized for its potential to improve the performance of surgical interventions, its moderate investment and operating costs and its portability. Although the technology is now mature, there is currently the problem of the availability of contrast agents to be injected IV. The aim of this methodology article is to propose an alternative solution to the need for contrast agents for clinical research, particularly in oncology. Methodology: They consist of coupling a fluorescent marker in the form of an NHS derivative, such as IR DYE manufactured in compliance with GMP, with therapeutic monoclonal antibodies having marketing authorization for molecular imaging. For a given antibody, the marking procedure must be the subject of a validation file on the final preparation filtered on a sterilizing membrane at 0.22 μm. Once the procedure has been validated, it would be unnecessary to repeat the tests before each clinical research examination. A check of the marking by thin-layer chromatography (TLC) and place it in a sample bank at +4˚C for 1 month of each injected formulation would be sufficient for additional tests if necessary. Conclusion: Molecular near-infrared fluorescence imaging is experiencing development, the process of which could be accelerated by greater availability of clinical contrast agents. Alternative solutions are therefore necessary to promote clinical research in this area. These methods must be shared to make it easier for researchers.

Contrastive Consistency and Attentive Complementarity for Deep Multi-View Subspace Clustering

Deep multi-view subspace clustering (DMVSC) based on self-expression has attracted increasing attention dueto its outstanding performance and nonlinear application. However, most existing methods neglect that viewprivatemeaningless information or noise may interfere with the learning of self-expression, which may lead to thedegeneration of clustering performance. In this paper, we propose a novel framework of Contrastive Consistencyand Attentive Complementarity (CCAC) for DMVsSC. CCAC aligns all the self-expressions of multiple viewsand fuses them based on their discrimination, so that it can effectively explore consistent and complementaryinformation for achieving precise clustering. Specifically, the view-specific self-expression is learned by a selfexpressionlayer embedded into the auto-encoder network for each view. To guarantee consistency across views andreduce the effect of view-private information or noise, we align all the view-specific self-expressions by contrastivelearning. The aligned self-expressions are assigned adaptive weights by channel attention mechanism according totheir discrimination. Then they are fused by convolution kernel to obtain consensus self-expression withmaximumcomplementarity ofmultiple views. Extensive experimental results on four benchmark datasets and one large-scaledataset of the CCAC method outperformother state-of-the-artmethods, demonstrating its clustering effectiveness.

Laser speckle contrast imaging to predict the effect of temporary spinal cord stimulation in postherpetic neuralgia patients: A prospective observational study

Temporary spinal cord stimulation(tSCS)can effectively reduce the pain and severity of postherpetic neuralgia(PHN).However,there are no effective and objective methods for predicting the effects of tSCS on PHN.Laser speckle contrast imaging(LSCI)is frequently used in neurology to evaluate the effectiveness of treatment.To assess the accuracy of LSCI in predicting the impact of tSCS on PHN,14 adult patients receiving tSCS treatments for spinal nerve-innervated(C6-T2)PHN participated in this observational study.Visual analog scale(VAS)assessments and LSCI bloodflow images of the-ngers were recorded after the tSCS procedure.The results showed that the VAS scores of all patients decreased signi-cantly.Moreover,the bloodflow index(BFI)values were signi-cantly higher than they were before the procedure.Increased bloodflow and pain alleviation were positively correlated.The-ndings indicated that spinal nerve PHN(C6-T2)was signi-cantly reduced by tSCS.Pain alleviation by tSCS was positively correlated with increased bloodflow in the hand.The effect of tSCS on PHN may thus be predicted using an independent and consistent indicator such as LSCI.

Assessment of desertification sensitivity using an improved MEDALUS model in Northern China

Assessment of land sensitivity to desertification is an important step to support desertification monitoring and control.Based on the Mediterranean Desertification and Land Use(MEDALUS)model,we defined four quality indicators(soil,climate,vegetation and management)to evaluate the sensitivity of land in northern China to desertification.We improved MEDALUS via excluding cities from the areas at risk of desertification by means of defining a threshold value for population density.The framework,validated in northern China,further optimizes the model to link priority areas and land restoration programmed to support desertification control.We found that the four indicators influenced and restricted each other,which jointly affected the distribution of desertification sensitivity in northern China.The spatial distribution of sensitivity in northern China showed large regional differences,with clear boundaries and concentrated distributions of regions with high and low sensitivity;the overall sensitivity decreased,with some areas rated as having moderate,severe,and extremely severe sensitivity changing to slight sensitivity;and the influence weight was much higher for the management quality index than for the climate,vegetation,and soil indexes.This suggests that management was the main factor that affected desertification sensitivity in northern China,and that climate factors exacerbated sensitivity,but the factors that are driving the spatial heterogeneity of the influencing factors need further study。