A polarization sensitive interferometer:Delta interferometer

A new type of polarization sensitive interferometer is proposed,named the Delta interferometer,inspired by its geometry resembling the Greek letter Delta.The main difference between the Delta interferometer and other existing interferometers,such as Michelson,Mach-Zehnder and Young's double-slit interferometers,is that the two interfering paths are asymmetrical in the Delta interferometer.The visibility of the first-order interference pattern observed in the Delta interferometer is dependent on the polarization of the incidental light.Optical coherence theory is employed to interpret this phenomenon and single-mode continuous-wave laser light is employed to verify the theoretical predictions.The theoretical and experimental results are consistent.The Delta interferometer is a perfect tool to study the reflection of electromagnetic fields in different polarizations and may find applications in polarization-sensitive scenarios.

Construction of a predictive model for gastric cancer neuroaggression and clinical validation analysis: A single-center retrospective study

BACKGROUND This study investigated the construction and clinical validation of a predictive model for neuroaggression in patients with gastric cancer.Gastric cancer is one of the most common malignant tumors in the world,and neuroinvasion is the key factor affecting the prognosis of patients.However,there is a lack of systematic analysis on the construction and clinical application of its prediction model.This study adopted a single-center retrospective study method,collected a large amo-unt of clinical data,and applied statistics and machine learning technology to build and verify an effective prediction model for neuroaggression,with a view to providing scientific basis for clinical treatment decisions and improving the tr-eatment effect and survival rate of patients with gastric cancer.AIM To investigate the value of a model based on clinical data,spectral computed to-mography(CT)parameters and image omics characteristics for the preoperative prediction of nerve invasion in patients with gastric cancer.METHODS A retrospective analysis was performed on 80 gastric cancer patients who under-went preoperative energy spectrum CT at our hospital between January 2022 and August 2023,these patients were divided into a positive group and a negative group according to their pathological results.Clinicopathological data were collected,the energy spectrum parameters of primary gastric cancer lesions were measured,and single factor analysis was performed.A total of 214 image omics features were extracted from two-phase mixed energy images,and the features were screened by single factor analysis and a support vector machine.The variables with statist-ically significant differences were included in logistic regression analysis to construct a prediction model,and the performance of the model was evaluated using the subject working characteristic curve.There were statistically significant differences in sex,carbohydrate antigen 199 expression,tumor thickness,Lauren classification and Borrmann classification between the two groups(all P<0.05).Among the energy spectrum parameters,there were statistically significant differences in the single energy values(CT60-CT110 keV)at the arterial stage between the two groups(all P<0.05)and statistically significant differences in CT values,iodide group values,standardized iodide group values and single energy values except CT80 keV at the portal vein stage between the two groups(all P<0.05).The support vector machine model with the largest area under the curve was selected by image omics analysis,and its area under the curve,sensitivity,specificity,accuracy,P value and pa-rameters were 0.843,0.923,0.714,0.925,<0.001,and c:g 2.64:10.56,respectively.Finally,based on the logistic regression algorithm,a clinical model,an energy spectrum CT model,an imaging model,a clinical+energy spe-ctrum model,a clinical+imaging model,an energy spectrum+imaging model,and a clinical+energy spectrum+imaging model were established,among which the clinical+energy spectrum+imaging model had the best efficacy in diagnosing gastric cancer nerve invasion.The area under the curve,optimal threshold,Youden index,sensitivity and specificity were 0.927(95%CI:0.850-1.000),0.879,0.778,0.778,and 1.000,respectively.CONCLUSION The combined model based on clinical features,spectral CT parameters and imaging data has good value for the preoperative prediction of gastric cancer neuroinvasion.

泪液渗透压在干眼发病机制中的作用及诊疗进展

干眼是一种以眼表稳态丧失,泪膜不稳定性增加为特征的多因素疾病,伴有眼干涩、异物感、灼烧感、眼红、疼痛、畏光、流泪、眼疲劳、视力下降、分泌物增多、对外界刺激敏感等眼部症状,其病理生理机制主要是泪膜不稳定、泪液渗透压(tear osmolarity, Tosm)升高、眼表炎症和损伤及神经感觉异常。Tosm是维持泪膜稳定性和眼表舒适度的重要因素。Tosm升高可造成干眼患者眼部不适、角膜上皮损伤、杯状细胞丢失及眼部炎症反应,炎症反应可进一步降低泪膜稳定性和增加Tosm,使干眼陷入恶性循环。为了更全面地了解泪液高渗(tear hyperosmolarity, THO)与干眼的关系,本文将从病理生理学方面,重点讨论THO在干眼发病机制、干眼诊断、干眼严重程度分级中的作用,及其针对性治疗。

Prognostic significance of preoperative fibrinogen in patients with colon cancer

AIM: To investigate the prognostic significance of preoperative fibrinogen levels in colon cancer patients.

Correlation between Helicobacter pylori-associated gastric diseases and colorectal neoplasia

AIM: To explore the correlation between Helicobacter pylori(H. pylori)-associated gastric diseases and colorectal neoplasia.METHODS: Patients included in this study underwent a colonoscopy and esophago-gastro-duodenoscopy(EGD) along with histopathological measurement between March 2012 and March 2015 at Qi-Lu Hospital of Shandong University, who also had results of H. pylori detection. A total of 233 cases were selected. Demographic data, H. pylori infection status(including results of rapid urease tests and gastric mucosa pathological examinations) and histopathological examination results of gastric and colorectal mucosa were gathered and analyzed. The statistical analysis focused on the prevalence of colorectal neoplasms among patients with various histopathological categories of the stomach. ORs and their 95%CI were calculated to describe the strengths of the associations.RESULTS: The incidence rates of colorectal adenoma without high-grade intraepithelial neoplasia(HGIEN)(OR = 2.400, 95%CI: 0.969-5.941), adenoma with HGIEN(5.333, 1.025-27.758) and adenocarcinoma(1.455, 0.382-5.543) were all higher for patients with H. pylori-associated gastritis than for those in the control group. The incidence rate of colorectal adenoma with HGIEN(3.218, 0.767-13.509) was higher in patients with intestinal metaplasia than in the control group, while the incidence rates of adenoma without HGIEN(0.874, 0.414-1.845) and adenocarcinoma(0.376, 0.096-1.470) were lower in the intestinal metaplasia group than in the control group. The incidence rate of colorectal adenoma without HGIEN(3.111, 1.248-7.753) was significantly higher in the gastric intraepithelial neoplasia group than in the control group, while the rates of adenoma with HGIEN(1.481, 0.138-15.941) and adenocarcinoma(2.020, 0.561-7.272) were higher in the gastric intraepithelial neoplasia group. Incidence rates of colorectal adenoma without HGIEN(1.067, 0.264-4.314), adenoma with HGIEN(2.667, 0.231-30.800) and adenocarcinoma(2.182, 0.450-10.585) were all higher in the gastric adenocarcinoma group than in the control group.CONCLUSION: H. pylori infection as well as H. pylori-associated gastric diseases are risk factors for colorectal neoplasia.

Experience of Clinical Management for Pregnant Women and Newborns with Novel Coronavirus Pneumonia in Tongji Hospital,China

Based on the New Diagnosis and Treatment Scheme for Novel Coronavirus Infected Pneumonia(Trial Edition 5),combined with our current clinical treatment experience,we recently proposed a revision of the first edition of“Guidance for maternal and fctal management during pneumonia epidemics of novel coronavirus infection in the Wuhan Tongji Hospital".This article focused on the issues of greatest concern of pregnant women including severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)infection diagnostic criteria,inspection precautions,drug treatment options,indications and methods of termination of pregnancy,postpartum fever,breastfeeding considerations,mode of mother-to-child transmission,neonatal isolation and advice on nconatal nursing,to provide valuable experience for better management of SARS-CoV-2 infection in pregnant women and newborns.

Comparison of intraosseous access and central venous catheterization in Chinese adult emergency patients: A prospective, multicenter, and randomized study

BACKGROUND: It is challenging to establish peripheral intravenous access in adult critically patients. This study aims to compare the success rate of the first attempt, procedure time, operator satisfaction with the used devices, pain score, and complications between intraosseous(IO) access and central venous catheterization(CVC) in critically ill Chinese patients.METHODS: In this prospective clustered randomized controlled trial, eight hospitals were randomly divided into either the IO group or the CVC group. Patients who needed emergency vascular access were included. From April 1, 2017 to December 31, 2018, each center included 12 patients. We recorded the data mentioned above.RESULTS: A total of 96 patients were enrolled in the study. There were no statistically significant differences between the two groups regarding sex, age, body mass index, or operator satisfaction with the used devices. The success rates of the first attempt and the procedure time were statistically significant between the IO group and the CVC group(91.7% vs. 50.0%, P<0.001;52.0 seconds vs. 900.0 seconds, P<0.001). During the study, 32 patients were conscious. There was no statistically significant difference between the two groups regarding the pain score associated with insertion. There were statistically significant differences between the two groups regarding the pain score associated with IO or CVC infusion(1.5 vs. 0.0, P=0.044). Complications were not observed in the two groups.CONCLUSIONS: IO access is a safe, rapid, and effective technique for gaining vascular access in critically ill adults with inaccessible peripheral veins in the emergency departments.

Fast Fourier single-pixel imaging based on Sierra–Lite dithering algorithm

The single-pixel imaging(SPI) technique is able to capture two-dimensional(2 D) images without conventional array sensors by using a photodiode. As a novel scheme, Fourier single-pixel imaging(FSI) has been proven capable of reconstructing high-quality images. Due to the fact that the Fourier basis patterns(also known as grayscale sinusoidal patterns)cannot be well displayed on the digital micromirror device(DMD), a fast FSI system is proposed to solve this problem by binarizing Fourier pattern through a dithering algorithm. However, the traditional dithering algorithm leads to low quality as the extra noise is inevitably induced in the reconstructed images. In this paper, we report a better dithering algorithm to binarize Fourier pattern, which utilizes the Sierra–Lite kernel function by a serpentine scanning method. Numerical simulation and experiment demonstrate that the proposed algorithm is able to achieve higher quality under different sampling ratios.

Structure-based multi-ligand molecular modeling to predict the synergistic effects of limonin and obacunone from Simiao pill against nitric oxide synthase 3 associated with hyperuricemia

Hyperuricemia(HUA)mainly occurs because of purine metabolism disorders.We recently proposed that limonin from Simiao pill may have therapeutic effects on nitric oxide synthase 3(NOS3)that is related to HUA.Concurrently,our previous work employed a new method,structure-based multi-ligand molecular modeling,to identify potential agents from a herbal formula that may produce synergistic effects and may have the potential to develop combination drugs.Therefore,we employed multi-ligand modeling to seek compounds with potential synergistic effects with limonin against NOS3.We obtained 403 multi-ligand docking results between 403 compounds and the limonin-NOS3 complex(average affinity–8.297 kcal/mol).Then we selected the top 10 highest binding affinity compounds for virtual pharmacokinetic and toxicity screening and we found that only obacunone passed all filters.We further subjected obacunone,bound to limonin and NOS3,to molecular dynamics simulations.We found that the NOS3-limonin-obacunone complex was more stable than the NOS3-limonin complex,based on the root mean square deviation of backbone Cαatoms and root mean square fluctuation,which suggests that synergistic effects may exist between limonin and obacunone.Further cell and animal experimental research is required to verify our results.

Coupling Co_(2)P nanoparticles onto N,P-doped biomass-derived carbon as efficient electrocatalysts for flexible Zn-air batteries

Catalysts for oxygen conversion play an important role in energy storage and conversion technologies such as metal-air batteries.Developing highly active stable,and low-cost catalysts is critical for further implementation of the above technologies.Herein,an efficien oxygen electrocatalyst with Co_(2)P nanoparticles(NPs)coupling onto N,P-doped porous carbon nanosheets(Co_(2)P@NPAC)derived from cotton stalk is successfully designed and prepared via activation,hydrothermal treatment,and pyrolysis procedure.The excellent properties of electrical conductivity,mass transfer,and synergistic integration between Co_(2)P and N,P-doped carbon endow Co_(2)P@NPAC composite with superior oxygen reduction reaction/oxygen evolution reaction(ORR/OER)performance.Co_(2)P@NPAC catalyst achieves ORR activity with half-wave potential of 0.85 V and high OER activity with overpotential of 261 mV at 10 mA·cm^(-2).The flexible Zn-air batteries(ZABs)based on Co_(2)P@NPAC catalyst revea outstanding performances with a high open-circuit voltage(1.38 V),a peak power density of(75 mW·cm^(-2)),and a low charge-discharge voltage gap(0.74 V,~200 cycles)The flexible ZABs express the stable discharge-charge voltage gap at various bending states.This work provides interesting inspiration for the ingenious design of efficien carbon electrocatalysts from biomass with potential application of energy storage and conversion devices.

Ultrafine Ru nanoparticles anchored on core-shell structured zeolite-carbon for efficient catalysis of hydrogen generation

As a promising route to hydrogen production,hydrolysis of ammonia borane(AB)aqueous solution requires efficient and stable catalysts.In this paper,a carbon-coated zeolite is prepared by high temperature calcination using glucose as carbon source.Ultrafine Ru nanoparticles are anchored on the composite support with core-shell structure using a simple in situ reduction method.The prepared catalyst expressed outstanding catalytic activity in the hydrolytic dehydrogenation of AB.The effects of support prepared by different synthesis parameters on the performance of catalyst are investigated.The Ru/S-1@C(RSC-2)catalyst exhibited the highest catalytic activity for hydrolytic dehydrogenation of AB with a turnover frequency of 892 min^(-1)at room temperature.This performance is superior to that of many catalysts previously reported.The excellent catalytic activity is attributed to the carbon layer on catalyst surface effectively limiting the aggregation of Ru nanoparticles in the hydrolysis reaction.The zeolite also plays a role in preactivation of water.This pre-activation accelerates the ratelimiting step of water dissociation in the reaction.The kinetic studies for determining the activation energy(E_(a)=36.8 kJ·mol^(-1))were based on reaction temperature.The effects of catalyst concentration,AB concentration and NaOH concentration on hydrolysis rate of AB were further investigated.The high-performance catalysts and the preparation method in this study have wide application prospects in the field of clean energy.

SICA for Cox's Proportional Hazards Model with a Diverging Number of Parameters

The smooth integration of counting and absolute deviation （SICA） penalized variable selection procedure for high-dimensional linear regression models is proposed by Lv and Fan （2009）. In this article, we extend their idea to Cox＇s proportional hazards （PH） model by using a penalized log partial likelihood with the SICA penalty. The number of the regression coefficients is allowed to grow with the sample size. Based on an approximation to the inverse of the Hessian matrix, the proposed method can be easily carried out with the smoothing quasi-Newton （SQN） algorithm. Under appropriate sparsity conditions, we show that the resulting estimator of the regression coefficients possesses the oracle property. We perform an extensive simulation study to compare our approach with other methods and illustrate it on a well known PBC data for predicting survival from risk factors.

Semiparametric Empirical Likelihood Estimation for Two-stage Outcome-dependent Sampling under the Frame of Generalized Linear Models

Epidemiologic studies use outcome-dependent sampling （ODS） schemes where, in addition to a simple random sample, there are also a number of supplement samples that are collected based on outcome variable. ODS scheme is a cost-effective way to improve study efficiency. We develop a maximum semiparametric empirical likelihood estimation （MSELE） for data from a two-stage ODS scheme under the assumption that given covariate, the outcome follows a general linear model. The information of both validation samples and nonvalidation samples are used. What is more, we prove the asymptotic properties of the proposed MSELE.

Optimal Generalized Case-Cohort Analysis with Cox's Proportional Hazards Model

Generalized case-cohort design has been proved to be a cost-effective way to enhance the efficiency of large epidemiological cohort. In this article, we propose an inference procedure for estimating the unknown parameters in Cox＇s proportional hazards model in generalized case-cohort design and establish an optimal sample size allocation to achieve the maximum power at a given budget. The finite sample performance of the proposed method is evaluated through simulation studies. The proposed method is applied to a real data set from the National Wilm＇s Tumor Study Group.

Additive Rate Model With Auxiliary Covariates

In this paper, we consider an inference method for recurrent event data in which the primary exposure covariate is assessed only in a validation set, while as an auxiliary covariate for the main exposure is available for the full cohort. Additive rate model is considered. The existing estimating equations in the absence of primary exposure are corrected by taking use of the validation data and auxiliary information, which yield consistent and asymptotically normal estimators of the regression parameters. The estimated baseline mean process is shown to converge weakly to a zero-mean Gaussian process. Extensive simulations are conducted to evaluate finite sample performance.

A pipelined Reed-Solomon decoder based on a modified step-by-step algorithm

We propose a pipelined Reed-Solomon(RS) decoder for an ultra-wideband system using a modified stepby-step algorithm. To reduce the complexity, the modified step-by-step algorithm merges two cases of the original algorithm. The pipelined structure allows the decoder to work at high rates with minimum delay. Consequently, for RS(23,17) codes, the proposed architecture requires 42.5% and 24.4% less area compared with a modified Euclidean architecture and a pipelined degree-computationless modified Euclidean architecture, respectively. The area of the proposed decoder is 11.3% less than that of the previous step-by-step decoder with a lower critical path delay.

Economic and employment effects of China's power transition based on input‒output and scenario simulation

With high carbon emission,the low-carbon transition of power sector will be critical for China to achieve the carbon peaking and carbon neutrality goals.The power transition will have an impact on the economy and employment through the value chain.Quantifying the impact is important for China's future energy and welfare policies.This study adopts input‒output model to analyze the impact on economy and employment based on accelerated and slow power transition scenarios.The results show that the low-carbon power transition will have a negative impact on coal power and coal mining and washing sectors,while a positive impact on machine manufacturing and equipment sector.Low-carbon power transition will have a positive economic and employment effect to promote inclusive growth.By 2060,economic output will increase by about 8.50 trillion CNY,value-added by about 3.39 trillion CNY,and employment will increase by about 3.74 million.Although slower coal power transition can stabilize the economic and employment effect in the short and medium run,accelerating the power transition will produce more positive effect and lower job losses by coal power in the long run.By 2060,accelerating transition will boost output by 8.21%,value-added by 8.20%and jobs by 7.97%.Accordingly,the government should establish an all-round just low-carbon transition mechanism.

The Proportional Mean Residual Life Regression Model with Cure Fraction and Auxiliary Covariate

As biological studies become more expensive to conduct,it is a frequently encountered question that how to take advantage of the available auxiliary covariate information when the exposure variable is not measured.In this paper,we propose an induced cure rate mean residual life time regression model to accommodate the survival data with cure fraction and auxiliary covariate,in which the exposure variable is only assessed in a validation set,but a corresponding continuous auxiliary covariate is ascertained for all subjects in the study cohort.Simulation studies elucidate the practical performance of the proposed method under finite samples.As an illustration,we apply the proposed method to a heart disease data from the Study of Left Ventricular Dysfunction.