Multi-dimensional multiplexing optical secret sharing framework with cascaded liquid crystal holograms

Secret sharing is a promising technology for information encryption by splitting the secret information into different shares.However,the traditional scheme suffers from information leakage in decryption process since the amount of available information channels is limited.Herein,we propose and demonstrate an optical secret sharing framework based on the multi-dimensional multiplexing liquid crystal(LC)holograms.The LC holograms are used as spatially separated shares to carry secret images.The polarization of the incident light and the distance between different shares are served as secret keys,which can significantly improve the information security and capacity.Besides,the decryption condition is also restricted by the applied external voltage due to the variant diffraction efficiency,which further increases the information security.In implementation,an artificial neural network(ANN)model is developed to carefully design the phase distribution of each LC hologram.With the advantage of high security,high capacity and simple configuration,our optical secret sharing framework has great potentials in optical encryption and dynamic holographic display.

Intelligent 6G Wireless Network with Multi-Dimensional Information Perception

Intelligence and perception are two operative technologies in 6G scenarios.The intelligent wireless network and information perception require a deep fusion of artificial intelligence(AI)and wireless communications in 6G systems.Therefore,fusion is becoming a typical feature and key challenge of 6G wireless communication systems.In this paper,we focus on the critical issues and propose three application scenarios in 6G wireless systems.Specifically,we first discuss the fusion of AI and 6G networks for the enhancement of 5G-advanced technology and future wireless communication systems.Then,we introduce the wireless AI technology architecture with 6G multidimensional information perception,which includes the physical layer technology of multi-dimensional feature information perception,full spectrum fusion technology,and intelligent wireless resource management.The discussion of key technologies for intelligent 6G wireless network networks is expected to provide a guideline for future research.

Detection of Multi-dimensional Driving Forces of Public Environmental Concern in China:Based on Spatial Heterogeneity Perspectives

Public environmental concern(PEC)is an important bottom-up force in building an environmentally sustainable society.Guided by attitude theory,this paper innovatively constructed a PEC evaluation index system,while introducing entropy weighted-TOPSIS(Technique for Order Preference by Similarity to Ideal Solution)to realize the assessment of PEC.Exploratory spatial data analysis was used to portray the spatio-temporal evolution patterns of PEC in 362 Chinese cities at prefecture-level and above from 2011 to 2018.Furthermore,the Geodetector model was performed to identify the multi-dimensional determinants of PEC from the perspective of spatial heterogeneity.The results indicated that:1)PEC in China exhibited a fluctuating upward trend,consistent with the spatial distribution law of‘Heihe-Tengchong Line’and‘Bole-Taipei Line’;2)the driving effect of each factor varied dynamically,but in general,economic development level,population size,industrial wastewater,and education level were the dominant driving factors explaining the spatial variation of PEC;3)risk detection revealed that four factors,government environmental regulations,PM_(2.5),vegetation coverage,and natural resource endowment,had nonlinear effects on PEC;4)the interactions between factors all demonstrated an enhancement in explaining the spatial differentiation of PEC.PEC was driven by the comprehensive interaction of four-dimensional factors of economy,society,pollutant emissions,and ecology.Among them,population agglomeration accompanied by a high level of regional economy and information technology can explain the increase in PEC to the greatest extent.

Envelope Method and More General New Global Structures of Solutions for Multi-dimensional Conservation Law

For the two-dimensional(2D)scalar conservation law,when the initial data contain two different constant states and the initial discontinuous curve is a general curve,then complex structures of wave interactions will be generated.In this paper,by proposing and investigating the plus envelope,the minus envelope,and the mixed envelope of 2D non-selfsimilar rarefaction wave surfaces,we obtain and the prove the new structures and classifications of interactions between the 2D non-selfsimilar shock wave and the rarefaction wave.For the cases of the plus envelope and the minus envelope,we get and prove the necessary and sufficient criterion to judge these two envelopes and correspondingly get more general new structures of 2D solutions.

Research and Practice on the Multi-dimensional Course Goal Achievement Evaluation of Software Engineering

According to the standards of engineering education accreditation,the achievement paths and evaluation criteria of course goals are presented,aimed at the objectives of software engineering courses and the characteristics of hybrid teaching in Kunming University of Science and Technology.Then a multi-dimensional evaluation system for course goal achievement of software engineering is proposed.The practice’s results show that the multi-dimensional course goal achievement evaluation is helpful to the continuous improvement of course teaching,which can effectively support the evaluation of graduation outcomes.

An Ordinal Multi-Dimensional Classification(OMDC)for Predictive Maintenance

Predictive Maintenance is a type of condition-based maintenance that assesses the equipment's states and estimates its failure probability and when maintenance should be performed.Although machine learning techniques have been frequently implemented in this area,the existing studies disregard to the nat-ural order between the target attribute values of the historical sensor data.Thus,these methods cause losing the inherent order of the data that positively affects the prediction performances.To deal with this problem,a novel approach,named Ordinal Multi-dimensional Classification(OMDC),is proposed for estimating the conditions of a hydraulic system's four components by taking into the natural order of class values.To demonstrate the prediction ability of the proposed approach,eleven different multi-dimensional classification algorithms(traditional Binary Relevance(BR),Classifier Chain(CC),Bayesian Classifier Chain(BCC),Monte Carlo Classifier Chain(MCC),Probabilistic Classifier Chain(PCC),Clas-sifier Dependency Network(CDN),Classifier Trellis(CT),Classifier Dependency Trellis(CDT),Label Powerset(LP),Pruned Sets(PS),and Random k-Labelsets(RAKEL))were implemented using the Ordinal Class Classifier(OCC)algorithm.Besides,seven different classification algorithms(Multilayer Perceptron(MLP),Support Vector Machine(SVM),k-Nearest Neighbour(kNN),Decision Tree(C4.5),Bagging,Random Forest(RF),and Adaptive Boosting(AdaBoost))were chosen as base learners for the OCC algorithm.The experimental results present that the proposed OMDC approach using binary relevance multi-dimensional classification methods predicts the conditions of a hydraulic system's multiple components with high accuracy.Also,it is clearly seen from the results that the OMDC models that utilize ensemble-based classification algorithms give more reliable prediction performances with an average Hamming score of 0.853 than the others that use traditional algorithms as base learners.

Data inversion of multi-dimensional magnetic resonance in porous media

Since its inception in the 1970s,multi-dimensional magnetic resonance(MR)has emerged as a powerful tool for non-invasive investigations of structures and molecular interactions.MR spectroscopy beyond one dimension allows the study of the correlation,exchange processes,and separation of overlapping spectral information.The multi-dimensional concept has been re-implemented over the last two decades to explore molecular motion and spin dynamics in porous media.Apart from Fourier transform,methods have been developed for processing the multi-dimensional time-domain data,identifying the fluid components,and estimating pore surface permeability via joint relaxation and diffusion spectra.Through the resolution of spectroscopic signals with spatial encoding gradients,multi-dimensional MR imaging has been widely used to investigate the microscopic environment of living tissues and distinguish diseases.Signals in each voxel are usually expressed as multi-exponential decay,representing microstructures or environments along multiple pore scales.The separation of contributions from different environments is a common ill-posed problem,which can be resolved numerically.Moreover,the inversion methods and experimental parameters determine the resolution of multi-dimensional spectra.This paper reviews the algorithms that have been proposed to process multidimensional MR datasets in different scenarios.Detailed information at the microscopic level,such as tissue components,fluid types and food structures in multi-disciplinary sciences,could be revealed through multi-dimensional MR.

Spectral purification improves monitoring accuracy of the comprehensive growth evaluation index for film-mulched winter wheat

In order to further improve the utility of unmanned aerial vehicle(UAV)remote-sensing for quickly and accurately monitoring the growth of winter wheat under film mulching, this study examined the treatments of ridge mulching,ridge–furrow full mulching, and flat cropping full mulching in winter wheat.Based on the fuzzy comprehensive evaluation (FCE) method, four agronomic parameters (leaf area index, above-ground biomass, plant height, and leaf chlorophyll content) were used to calculate the comprehensive growth evaluation index (CGEI) of the winter wheat, and 14 visible and near-infrared spectral indices were calculated using spectral purification technology to process the remote-sensing image data of winter wheat obtained by multispectral UAV.Four machine learning algorithms, partial least squares, support vector machines, random forests, and artificial neural network networks(ANN), were used to build the winter wheat growth monitoring model under film mulching, and accuracy evaluation and mapping of the spatial and temporal distribution of winter wheat growth status were carried out.The results showed that the CGEI of winter wheat under film mulching constructed using the FCE method could objectively and comprehensively evaluate the crop growth status.The accuracy of remote-sensing inversion of the CGEI based on the ANN model was higher than for the individual agronomic parameters, with a coefficient of determination of 0.75,a root mean square error of 8.40, and a mean absolute value error of 6.53.Spectral purification could eliminate the interference of background effects caused by mulching and soil, effectively improving the accuracy of the remotesensing inversion of winter wheat under film mulching, with the best inversion effect achieved on the ridge–furrow full mulching area after spectral purification.The results of this study provide a theoretical reference for the use of UAV remote-sensing to monitor the growth status of winter wheat with film mulching.

Association between triglyceride-glucose index and colorectal polyps:A retrospective cross-sectional study

BACKGROUND Colorectal polyps(CPs)are frequently occurring abnormal growths in the colorectum,and are a primary precursor of colorectal cancer(CRC).The triglyceride-glucose(TyG)index is a novel marker that assesses metabolic health and insulin resistance,and has been linked to gastrointestinal cancers.AIM To investigate the potential association between the TyG index and CPs,as the relation between them has not been documented.METHODS A total of 2537 persons undergoing a routine health physical examination and colonoscopy at The First People's Hospital of Kunshan,Jiangsu Province,China,between January 2020 and December 2022 were included in this retrospective cross-sectional study.After excluding individuals who did not meet the eligibility criteria,descriptive statistics were used to compare characteristics between patients with and without CPs.Logistic regression analyses were conducted to determine the associations between the TyG index and the prevalence of CPs.The TyG index was calculated using the following formula:Ln[triglyceride(mg/dL)×glucose(mg/dL)/2].The presence and types of CPs was determined based on data from colonoscopy reports and pathology reports.RESULTS A nonlinear relation between the TyG index and the prevalence of CPs was identified,and exhibited a curvilinear pattern with a cut-off point of 2.31.A significant association was observed before the turning point,with an odds ratio(95% confidence interval)of 1.70(1.40,2.06),P<0.0001.However,the association between the TyG index and CPs was not significant after the cut-off point,with an odds ratio(95% confidence interval)of 0.57(0.27,1.23),P=0.1521.CONCLUSION Our study revealed a curvilinear association between the TyG index and CPs in Chinese individuals,suggesting its potential utility in developing colonoscopy screening strategies for preventing CRC.

A phenology-based vegetation index for improving ratoon rice mapping using harmonized Landsat and Sentinel-2 data

Ratoon rice,which refers to a second harvest of rice obtained from the regenerated tillers originating from the stubble of the first harvested crop,plays an important role in both food security and agroecology while requiring minimal agricultural inputs.However,accurately identifying ratoon rice crops is challenging due to the similarity of its spectral features with other rice cropping systems(e.g.,double rice).Moreover,images with a high spatiotemporal resolution are essential since ratoon rice is generally cultivated in fragmented croplands within regions that frequently exhibit cloudy and rainy weather.In this study,taking Qichun County in Hubei Province,China as an example,we developed a new phenology-based ratoon rice vegetation index(PRVI)for the purpose of ratoon rice mapping at a 30 m spatial resolution using a robust time series generated from Harmonized Landsat and Sentinel-2(HLS)images.The PRVI that incorporated the red,near-infrared,and shortwave infrared 1 bands was developed based on the analysis of spectro-phenological separability and feature selection.Based on actual field samples,the performance of the PRVI for ratoon rice mapping was carefully evaluated by comparing it to several vegetation indices,including normalized difference vegetation index(NDVI),enhanced vegetation index(EVI)and land surface water index(LSWI).The results suggested that the PRVI could sufficiently capture the specific characteristics of ratoon rice,leading to a favorable separability between ratoon rice and other land cover types.Furthermore,the PRVI showed the best performance for identifying ratoon rice in the phenological phases characterized by grain filling and harvesting to tillering of the ratoon crop(GHS-TS2),indicating that only several images are required to obtain an accurate ratoon rice map.Finally,the PRVI performed better than NDVI,EVI,LSWI and their combination at the GHS-TS2 stages,with producer's accuracy and user's accuracy of 92.22 and 89.30%,respectively.These results demonstrate that the proposed PRVI based on HLS data can effectively identify ratoon rice in fragmented croplands at crucial phenological stages,which is promising for identifying the earliest timing of ratoon rice planting and can provide a fundamental dataset for crop management activities.

Hash-Indexing Block-Based Deduplication Algorithm for Reducing Storage in the Cloud

Cloud storage is essential for managing user data to store and retrieve from the distributed data centre.The storage service is distributed as pay a service for accessing the size to collect the data.Due to the massive amount of data stored in the data centre containing similar information and file structures remaining in multi-copy,duplication leads to increase storage space.The potential deduplication system doesn’t make efficient data reduction because of inaccuracy in finding similar data analysis.It creates a complex nature to increase the storage consumption under cost.To resolve this problem,this paper proposes an efficient storage reduction called Hash-Indexing Block-based Deduplication(HIBD)based on Segmented Bind Linkage(SBL)Methods for reducing storage in a cloud environment.Initially,preprocessing is done using the sparse augmentation technique.Further,the preprocessed files are segmented into blocks to make Hash-Index.The block of the contents is compared with other files through Semantic Content Source Deduplication(SCSD),which identifies the similar content presence between the file.Based on the content presence count,the Distance Vector Weightage Correlation(DVWC)estimates the document similarity weight,and related files are grouped into a cluster.Finally,the segmented bind linkage compares the document to find duplicate content in the cluster using similarity weight based on the coefficient match case.This implementation helps identify the data redundancy efficiently and reduces the service cost in distributed cloud storage.

On traceable iterated line graph and hamiltonian path index

Xiong and Liu[21]gave a characterization of the graphs G for which the n-iterated line graph L^(n)(G)is hamiltonian,for n≥2.In this paper,we study the existence of a hamiltonian path in L^(n)(G),and give a characterization of G for which L^(n)(G)has a hamiltonian path.As applications,we use this characterization to give several upper bounds on the hamiltonian path index of a graph.

An evaluation of ureteral diameter ratio and vesicoureteral reflux index in the treatment of primary vesicoureteral reflux

Objective:Vesicoureteral reflux(VUR)index is a simple,validated tool that reliably predicts significant improvement and spontaneous resolution of primary reflux in children.The aim of this study was to evaluate and compare the ureter diameter ratio(UDR)and VUR index(VURx)of patients treated with endoscopic injection(EI)and ureteroneocystostomy(UNC)methods in the pediatric age group due to primary VUR.Methods:Patients under the age of 18 years old who underwent EI and UNC with the diagnosis of primary VUR between January 2011 and September 2021 were determined as the participants.The UDR was assessed using voiding cystourethrography,and the VURx score was determined prior to treatment based on hospital records included in the study.Results:A total of 255 patients,60(23.5%)boys and 195(76.5%)girls,with a mean age of 76.5(range 13.0e204.0)months,were included in the study.EI was applied to 130(51.0%)patients and UNC was applied to 125(49.0%)patients due to primary VUR.The optimum cut-off for the distal UDR was obtained as 0.17 with sensitivity and specificity of 73.0%and 63.0%,respectively.The positive and negative predictive values were 66.0%and 70.0%,respectively.Conclusion:When the UDR and VURx score are evaluated together for the surgical treatment of primary VUR in the pediatric age group,it is thought that it may be useful in predicting the clinical course of the disease and evaluating surgical treatment options.

Association between the cumulative triglyceride-glucose index and the recurrence of atrial fibrillation after radiofrequency catheter ablation

BACKGROUND Triglyceride-glucose(TyG)index values are a new surrogate marker for insulin resistance.This study aimed to explore the relationship between cumulative TyG index values and atrial fibrillation(AF)recurrence after radiofrequency catheter ablation(RFCA).METHODS A total of 576 patients with AF who underwent RFCA at the Second Affiliated Hospital of Xi'an Jiaotong University were included in this study.The participants were grouped based on cumulative TyG index values tertiles within 3 months after ablation.Cox regression and restricted cubic spline analyses were used to determine the relationship between cumulative TyG index values and AF recurrence.The predictive value of all risk factors was assessed by receiver operating curve analysis.RESULTS There were 375 patients completed the study(age:63.23±10.73 years,64.27%male).The risk of AF recurrence increased with increasing cumulative TyG index values tertiles.After adjusting for potential confounders,patients in the medium cumulative TyG index group[hazard ratio(HR)=4.949,95%CI:1.778–13.778,P=0.002]and the high cumulative TyG index group(HR=8.716,95%CI:3.371–22.536,P<0.001)had a higher risk of AF recurrence than those in the low cumulative TyG index group.The restricted cubic spline regression model also showed an increased risk of AF recurrence with increasing cumulative TyG index values.When considering cumulative TyG index values,left atrial diameter,and lactate dehydrogenase levels as a comprehensive factor,the model could effectively predict AF recurrence after RFCA[area under the curve(AUC)=0.847,95%CI:0.797–0.897,P<0.001].CONCLUSIONS Cumulative TyG index values were a risk factor for AF recurrence after RFCA.Monitoring longitudinal TyG index values may assist with optimized for risk stratification and outcome prediction for AF recurrence.

Early peripheral perfusion index predicts 28-day outcome in patients with septic shock

BACKGROUND:To investigate the prognostic value of the peripheral perfusion index(PPI)in patients with septic shock.METHODS:This prospective cohort study,conducted at the emergency intensive care unit of Peking University People's Hospital,recruited 200 patients with septic shock between January 2023 and August 2023.These patients were divided into survival(n=84)and death(n=116)groups based on 28-day outcomes.Clinical evaluations included laboratory tests and clinical scores,with lactate and PPI values assessed upon admission to the emergency room and at 6 h and 12 h after admission.Risk factors associated with mortality were analyzed using univariate and multivariate Cox regression analyses.Receiver operator characteristic(ROC)curve was used to assess predictive performance.Mortality rates were compared,and Kaplan-Meier survival plots were created.RESULTS:Compared to the survival group,patients in the death group were older and had more severe liver damage and coagulation dysfunction,necessitating higher norepinephrine doses and increased fl uid replacement.Higher lactate levels and lower PPI levels at 0 h,6 h,and 12 h were observed in the death group.Multivariate Cox regression identifi ed prolonged prothrombin time(PT),decreased 6-h PPI and 12-h PPI as independent risk factors for death.The area under the curves for 6-h PPI and 12-h PPI were 0.802(95%CI 0.742-0.863,P<0.001)and 0.945(95%CI 0.915-0.974,P<0.001),respectively,which were superior to Glasgow Coma Scale(GCS),Sequential Organ Failure Assessment(SOFA)scores(0.864 and 0.928).Cumulative mortality in the low PPI groups at 6 h and 12 h was signifi cantly higher than in the high PPI groups(6-h PPI:77.52%vs.22.54%;12-h PPI:92.04%vs.13.79%,P<0.001).CONCLUSION:PPI may have value in predicting 28-day mortality in patients with septic shock.

Actuality and underlying mechanisms of systemic immuneinflammation index and geriatric nutritional risk index prognostic value in hepatocellular carcinoma

This editorial contains comments on the article“Correlation between preoperative systemic immune inflammation index,nutritional risk index,and prognosis of radical resection of liver cancer”in a recent issue of the World Journal of Gastrointestinal Surgery.It pointed out the actuality and importance of the article and focused primarily on the underlying mechanisms making the systemic immuneinflammation index(SII)and geriatric nutritional risk index(GNRI)prediction features valuable.There are few publications on both SII and GNRI together in hepatocellular carcinoma(HCC)and patient prognosis after radical surgery.Neutrophils release cytokines,chemokines,and enzymes,degrade extracellular matrix,reduce cell adhesion,and create conditions for tumor cell invasion.Neutrophils promote the adhesion of tumor cells to endothelial cells,through physical anchoring.That results in the migration of tumor cells.Pro-angiogenic factors from platelets enhance tumor angiogenesis to meet tumor cell supply needs.Platelets can form a protective film on the surface of tumor cells.This allows avoiding blood flow damage as well as immune system attack.It also induces the epithelial-mesenchymal transformation of tumor cells that is critical for invasiveness.High SII is also associated with macro-and microvascular invasion and increased numbers of circulating tumor cells.A high GNRI was associated with significantly better progression-free and overall survival.HCC patients are a very special population that requires increased attention.SII and GNRI have significant survival prediction value in both palliative treatment and radical surgery settings.The underlying mechanisms of their possible predictive properties lie in the field of essential cancer features.Those features provide tumor nutrition,growth,and distribution throughout the body,such as vascular invasion.On the other hand,they are tied to the possibility of patients to resist tumor progression and development of complications in both postoperative and cancer-related settings.The article is of considerable interest.It would be helpful to continue the study follow-up to 2 years and longer.External validation of the data is needed.

A Transparent Photoresist Made of Titanium Dioxide Nanoparticle-Embedded Acrylic Resin with a Tunable Refractive Index for UV-Imprint Lithography

Transparent photoresists with a high refractive index(RI)and high transmittance in visible wavelengths have promising functionalities in optical fields.This work reports a kind of tunable optical material composed of titanium dioxide nanoparticles embedded in acrylic resin with a high RI for ultraviolet(UV)-imprint lithography.The hybrid film exhibits a tunable RI of up to 1.67(589 nm)after being cured by UV light,while maintaining both a high transparency of over 98%in the visible light range and a low haze of less than 0.05%.The precision machining of optical microstructures can be imprinted easily and efficiently using the hybrid resin,which acts as a light guide plate(LGP)to guide the light from the side to the top in order to conserve the energy of the display device.These preliminary studies based on both laboratory and commercial experiments pave the way for exploiting the unparalleled optical properties of nanocomposite resins and promoting their industrial application.

Antecedent Precipitation Index to Estimate Soil Moisture and Correlate as a Triggering Process in the Occurrence of Landslides

Landslides are highly dangerous phenomena that occur in different parts of the world and pose significant threats to human populations. Intense rainfall events are the main triggering process for landslides in urbanized slope regions, especially those considered high-risk areas. Various other factors contribute to the process;thus, it is essential to analyze the causes of such incidents in all possible ways. Soil moisture plays a critical role in the Earth’s surface-atmosphere interaction systems;hence, measurements and their estimations are crucial for understanding all processes involved in the water balance, especially those related to landslides. Soil moisture can be estimated from in-situ measurements using different sensors and techniques, satellite remote sensing, hydrological modeling, and indicators to index moisture conditions. Antecedent soil moisture can significantly impact runoff for the same rainfall event in a watershed. The Antecedent Precipitation Index (API) or “retained rainfall,” along with the antecedent moisture condition from the Natural Resources Conservation Service, is generally applied to estimate runoff in watersheds where data is limited or unavailable. This work aims to explore API in estimating soil moisture and establish thresholds based on landslide occurrences. The estimated soil moisture will be compared and calibrated using measurements obtained through multisensor capacitance probes installed in a high-risk area located in the mountainous region of Campos do Jordão municipality, São Paulo, Brazil. The API used in the calculation has been modified, where the recession coefficient depends on air temperature variability as well as the climatological mean temperature, which can be considered as losses in the water balance due to evapotranspiration. Once the API is calibrated, it will be used to extrapolate to the entire watershed and consequently estimate soil moisture. By utilizing recorded mass movements and comparing them with API and soil moisture, it will be possible to determine thresholds, thus enabling anticipation of landslide occurrences.

Systemic immune-inflammation index,neutrophilto-lymphocyte ratio,and platelet-to-lymphocyte ratio in patients with type 2 diabetes at different stages of diabetic retinopathy

AIM:To investigate systemic immune-inflammation index(SII),neutrophil-to-lymphocyte ratio(NLR),and plateletto-lymphocyte ratio(PLR)levels in patients with type 2 diabetes at different stages of diabetic retinopathy(DR).METHODS:This retrospective study included 141 patients with type 2 diabetes mellitus(DM):45 without diabetic retinopathy(NDR),47 with non-proliferative diabetic retinopathy(NPDR),and 49 with proliferative diabetic retinopathy(PDR).Complete blood counts were obtained,and NLR,PLR,and SII were calculated.The study analysed the ability of inflammatory markers to predict DR using receiver operating characteristic(ROC)curves.The relationships between DR stages and SII,PLR,and NLP were assessed using multivariate logistic regression.RESULTS:The average NLR,PLR,and SII were higher in the PDR group than in the NPDR group(P=0.011,0.043,0.009,respectively);higher in the NPDR group than in the NDR group(P<0.001 for all);and higher in the PDR group than in the NDR group(P<0.001 for all).In the ROC curve analysis,the NLR,PLR,and SII were significant predictors of DR(P<0.001 for all).The highest area under the curve(AUC)was for the PLR(0.929 for PLR,0.925 for SII,and 0.821 for NLR).Multivariate regression analysis indicated that NLR,PLR,and SII were statistically significantly positive and independent predictors for the DR stages in patients with DM[odds ratio(OR)=1.122,95%confidence interval(CI):0.200–2.043,P<0.05;OR=0.038,95%CI:0.018–0.058,P<0.05;OR=0.007,95%CI:0.001–0.01,P<0.05,respectively).CONCLUSION:The NLR,PLR,and SII may be used as predictors of DR.

Fabrication of UV-Curing Linalool-Polysiloxane Hybrid Films with High Refractive Index and Transparency

In this article,a series of high refractive indices(1.50-1.53)thiol phenyl polysiloxane(TPS)were synthesized via hydrolytic sol-gel reaction.The Fourier transform infrared spectra(FT-IR)and nuclear magnetic resonance spectra(NMR)results showed that TPS conformed to the predicted structures.Natural terpene linalool was exploited as photocrosslinker to fabricate UV-curing linalool-polysiloxane hybrid films(LPH)with TPS via photoinitiated thiol-ene reaction.LPH rapidly cured under UV irradiation at the intensity of 80 mW/cm^(2) in 30 s,exhibiting good UV-curing properties.The optical transmittance of LPH in the wavelength of 300-800 nm was over 90%,exhibiting good optical transparency.The water contact angle and water vapor permeability results showed that the introduction of phenyl groups enhance the hydrophobicity and water vapor barrier properties of LPH.The results indicated the potential of LPHs in the applications of optical functional coatings.