GS评价指标在医疗绩效管理标准化中的应用

当前我国持续深化医疗体制改革,探索建立符合医疗行业特点的绩效评价制度。本文介绍了符合现代绩效管理先进理念、兼顾疾病复杂性与严重性的GS的绩效评价方法,并对公立医院医疗服务体系中传统绩效管理评价问题进行了具体分析,提出了GS评价指标在医疗绩效管理标准化中的应用策略,希望能够在综合评价医院工作人员的绩效和财务管理等工作中发挥较好的作用。

94份小麦种质Puroindoline和HMW-GS分子检测与品质分析

籽粒硬度和高分子量谷蛋白亚基(HMW-GS)对小麦品质起决定作用,为发掘和利用硬度Puroindoline基因和HMW-GS优异等位变异,提升长江中下游麦区中强筋小麦品质,对长江中下游麦区推广品种以及其他麦区优质推广品种和地方品种共计94份材料进行分子检测和品质分析。结果表明,硬度变幅7.21~72.91,软质类型42份、占44.68%,硬质类型42份、占44.68%,混合类型10份、占10.64%。硬度突变基因型共有5种,包括Pina-D1b/Pinb-D1a、Pina-D1r/Pinb-D1a、Pina-D1s/Pinb-D1a、Pina-D1a/Pinb-D1b和Pina-D1a/Pinb-D1p,数量分别为8份、3份、1份、29份和9份,籽粒硬度表现依次为Pina-D1r/Pinb-D1a>Pina-D1s/Pinb-D1a>Pina-D1b/Pinb-D1a>Pina-D1a/Pinb-D1p>Pina-D1a/Pinb-D1b。HMW-GS分析表明,Glu-A1位点1和Null亚基材料比例分别为53.33%和45.56%,此外有1G330E亚基材料1份;Glu-B1位点7+8和7+9亚基材料比例分别为47.78%和46.67%,此外有14+15亚基材料3份、7OE+8*亚基材料1份、6+8亚基材料1份;Glu-D1位点2+12和5+10亚基材料比例分别为61.11%和38.89%。在微量SDS沉淀值上,Glu-A1位点的1和Null亚基、Glu-B1位点的7+8和7+9亚基无显著差异,Glu-D1位点5+10亚基极显著大于2+12亚基。硬度和SDS沉淀值呈极显著正相关,硬度对SDS沉淀值影响大于HMW-GS。本研究对小麦种质Pin和HMW-GS基因型和品质进行了分析,为小麦品质遗传改良尤其是中强筋小麦品质改良提供了参考。

Life Cycle Assessment of Green Buildings Based on Grey Clustering Method

To promote and develop green buildings,a standardized,applicable and easily operable index system for the assessment of such buildings was established on the basis of life cycle cost effectiveness.From the perspectives of environment-friendly materials,water resource environment,energy and environment,quality of indoor and outdoor environment,operation and management,and economical efficiency of life cycle,a modified index system was built,AHP was applied to obtain weights of indexes,evaluation methods of the grey system were used to evaluate green buildings,case study was adopted to verify the practicability and scientificity of the method.The results showed that Grey Clustering Method was an objective and reliable tool to evaluate green buildings,the calculation was simple,practical and easily operable,and moreover,the assessment process could be optimized by computer programming to improve its efficiency and precision.

Grey Markov chain and its application in drift prediction model of FOGs

A novel grey Markov chain predictive model is discussed to reduce drift influence on the output of fiber optical gyroscopes (FOGs) and to improve FOGs' measurement precision. The proposed method possesses advantages of grey model and Markov chain. It makes good use of dynamic modeling idea of the grey model to predict general trend of original data. Then according to the trend, states are divided so that it can overcome the disadvantage of high computational cost of state transition probability matrix in Markov chain. Moreover, the presented approach expands the applied scope of the grey model and makes it be fit for prediction of random data with bigger fluctuation. The numerical results of real drift data from a certain type FOG verify the effectiveness of the proposed grey Markov chain model powerfully. The Markov chain is also investigated to provide a comparison with the grey Markov chain model. It is shown that the hybrid grey Markov chain prediction model has higher modeling precision than Markov chain itself, which prove this proposed method is very applicable and effective.

Intelligent back analysis of geotechnical parameters for time-dependent rock mass surrounding mine openings using grey Verhulst model

In this paper,we present a new method of intelligent back analysis(IBA)using grey Verhulst model(GVM)to identify geotechnical parameters of rock mass surrounding tunnel,and validate it via a test for a main openings of−600 m level in Coal Mine“6.13”,Democratic People's Republic of Korea.The displacement components used for back analysis are the crown settlement and sidewalls convergence monitored at the end of the openings excavation,and the final closures predicted by GVM.The non-linear relation between displacements and back analysis parameters was obtained by artificial neural network(ANN)and Burger-creep viscoplastic(CVISC)model of FLAC3D.Then,the optimal parameters were determined for rock mass surrounding tunnel by genetic algorithm(GA)with both groups of measured displacements at the end of the final excavation and closures predicted by GVM.The maximum absolute error(MAE)and standard deviation(Std)between calculated displacements by numerical simulation with back analysis parameters and in situ ones were less than 6 and 2 mm,respectively.Therefore,it was found that the proposed method could be successfully applied to determining design parameters and stability for tunnels and underground cavities,as well as mine openings and stopes.

蓟县地震台gPhone、DZW和GS-15重力仪重力噪声水平对比

选取蓟县地震台同址观测的3台不同型号重力仪(gPhone、DZW和GS-15)2022年全年的连续观测数据,研究不同类型仪器对环境噪声的响应,计算3种重力仪的重力噪声水平,同时计算地震频段(200~600 s)的地震噪声等级,并与全国gPhone重力仪的地震噪声等级进行对比。结果表明:1)在频率低于10-3 Hz时,扣除固体潮和气压改正可以明显改进重力噪声水平;2)相同台站不同仪器重力噪声水平不同,gPhone型重力仪的背景噪声水平低于DZW型重力仪和GS-15型重力仪,其SNM值为3.355;3)2022年全国gPhone重力仪的地震频段噪声水平均值为5.418,蓟县台的噪声水平平均值为3.465,低于全国的噪声水平。研究结果可为3类重力仪观测数据的研究应用提供参考。

Optimization of casting conditions for heat and abrasion resistant large grey iron castings

Numerical simulation technology was applied for optimizing the casting design and conditions in large cast iron castings for marine engine. By the simulation of mold filling and solidification sequences the problems of the previous casting conditions were analyzed and marked improvements for large cylinder liner parts were derived from these results. Especially the amount and positions of chills were optimized to increase the mechanical properties and to minimize the shrinkage and microporosity in the castings. Ultrasonic testing, penetration testing and mechanical property testing were carried out for the parts with the modified casting conditions. It showed that no defects in the castings were found and the productivity could be distinctly increased. The mechanical properties satisfied also the specification demanded.

Study of Potentiodynamic Polarization Behaviour of Electroless Ni-B Coatings and Optimization using Taguchi Method and Grey Relational Analysis

Electroless nickel coatings are very popular for their corrosion resistant actions. The present article attempts to study the corrosion behaviour of electroless Ni-B coatings by varying the coating parameters viz. bath temperature, reducing agent concentration and nickel source concentration together with the annealing temperature. The electrochemical parameters viz., corrosion potential and corrosion current density are evaluated with the help of potentiodynamic polarization experimentation. Taguchi based Grey analysis is employed in order to optimize this multiple response problem and the optimal combination of parameters for maximum corrosion resistance for Ni-B coatings is presented. Moreover, analysis of variance reveals that bath temperature and concentration of nickel source have significant influence on the corrosion performance of the coating. The microstructure characterization of the coating is also conducted with the help of scanning electron microscopy, energy dispersive X-ray analysis and X-ray diffraction analysis. The Ni-B coating in general exhibits a nodular structure and turns crystalline with heat treatment. The corroded surface exhibits cracks and black spots which imply the occurrence of localized corrosion.

Prediction of the maximum water inflow in Pingdingshan No.8 mine based on grey system theory

In order to prevent and control the water inflow of mines, this paper built a new initial GM（1, 1） model to torecast the maximum water inflow according to the principle of new information. The effect of the new initial GM（1, 1） model is not ideal by the concrete example. Then according to the principle of making the sum of the squares of the difference between the calculated sequences and the original sequences, an optimized GM（1, I） model was established. The result shows that this method is a new prediction method which can predict the maximum water inflow accurately. It not only conforms to the guide- line of prevention primarily, but also provides reference standards to managers on making prevention measures.

SALL4、GS、HSP70在肝癌组织中的表达及其在早筛中的临床价值

目的分析婆罗双树样基因4(SALL4)、谷氨酰胺合成酶(GS)、热休克蛋白70(HSP70)在肝癌组织中的表达及其在早筛中的临床价值。方法选取2020年7月至2023年6月三台县人民医院收治的153例原发性肝癌患者(肝癌组,Edmondson病理分级:Ⅰ~Ⅱ级58例,Ⅲ~Ⅳ级95例),以153例患者距肿瘤切缘>3 cm处癌旁组织作为对照组,以及同期良性肝病组织141例作为良性组。分析三组以及肝癌组不同分级患者SALL4蛋白、GS、HSP70表达情况,分析SALL4蛋白、GS、HSP70对肝癌早期诊断价值。结果SALL4蛋白、GS、HSP70在不同组织中阳性表达率均为:肝癌组>良性组>对照组,差异均有统计学意义(P<0.05);Ⅲ~Ⅳ级患者组织中SALL4蛋白、GS、HSP70表达阳性率均明显高于Ⅰ~Ⅱ级,差异均有统计学意义(P<0.05);依据ROC曲线可知,SALL4+GS+HSP70联合检测对肝癌早期诊断敏感度和特异度分别为95.10%、78.60%,AUC=0.838(95%CI:0.755~0.922),明显高于SALL4、GS、HSP70单独检测(P<0.05)。结论SALL4蛋白、GS、HSP70在肝癌组织中均为高表达,三者表达情况或可作为肝癌早期筛查的评估指标,在肝癌的早期诊断及病情评估中有重要的临床意义。

OBLF GS1000直读光谱仪测量碳素钢中硅含量的不确定度评定

通过OBLF GS1000直读光谱仪分析了各种不确定度分量在碳素钢中硅含量测定中的影响,提供了硅含量的测量不确定度评定过程中相关参数的采集方法和对应的计算方法。结果表明:在采用OBLF GS1000直读光谱仪测定碳素钢中硅含量的各种不确定度过程中,硅含量可表示为w(Si)=0.281 2%±0.007%(K=2);影响测量不确度最大的分量是标准物质定值分量,其次是样品测定分量引入的不确定度。

基于GS1 Digital Link的Web编码构建与案例应用

为探索GS1 Digital Link技术在产品物流中的应用潜力,分析研究了GS1系统和GS1 Digital Link的基本结构、编码特点以及技术优势,充分利用GS1 Digital Link技术可以为产品从源头到零售整个物流过程提供相关对象的Web地址编码的特点,以鲜活大闸蟹物流过程为例,构建了基于GS1 Digital Link的鲜活大闸蟹Web编码,为实现产品营销与追溯提供了标准化、动态化、多样化的编码数据支撑。

GS1系统在疫苗接种溯源中的应用研究

目的:应用GS1系统对疫苗赋码和管理进行身份定义,使用“智慧化追溯和接种系统”对疫苗储存、运输、分包、接种等环节进行追踪和交互,分析GS1在疫苗接种溯源中的实用性和可扩展性。方法:利用GS1+物联网+智慧化追溯和接种系统形成疫苗接种溯源体系,收集舟山市2018年12月至2020年11月的使用数据,对比评价GS1系统在疫苗接种使用情况。结果:通过GS1系统编码体系实践、应用,平台对49,800,350个疫苗进行赋码,对其中173,872条调拨和使用,共计关联冷链监测温度数据5,184,000条,系统接种疫苗27,789剂次,未出现接种差错和事故。结论:基于GS1系统的编码体系在疫苗赋码、储存、配送、接种使用、终端追踪等全过程跟踪追溯的实践中,满足疫苗接种溯源和数据交互等要求,能够覆盖疫苗生命周期的溯源需要。

Significant genomic introgression from grey junglefowl(Gallus sonneratii)to domestic chickens(Gallus gallus domesticus)

Background Chicken is one of the most numerous and widely distributed species around the world,and many studies support the multiple ancestral origins of domestic chickens.The research regarding the yellow skin phenotype in domestic chickens(regulated by BCO2)likely originating from the grey junglefowl serves as crucial evidence for demonstrating the multiple origins of chickens.However,beyond the BCO2 gene region,much remains unknown about the introgression from the grey junglefowl into domestic chickens.Therefore,in this study,based on wholegenome data of 149 samples including 4 species of wild junglefowls and 13 local domestic chicken breeds,we explored the introgression events from the grey junglefowl to domestic chickens.Results We successfully detected introgression regions besides BCO2,including two associated with growth trait(IGFBP2 and TKT),one associated with angiogenesis(TIMP3)and two members of the heat shock protein family(HSPB2 and CRYAB).Our findings suggest that the introgression from the grey junglefowl may impact the growth performance of chickens.Furthermore,we revealed introgression events from grey junglefowl at the BCO2 region in multiple domestic chicken breeds,indicating a phenomenon where the yellow skin phenotype likely underwent strong selection and was retained.Additionally,our haplotype analysis shed light on BCO2 introgression event from different sources of grey junglefowl into domestic chickens,possibly suggesting multiple genetic flows between the grey junglefowl and domestic chickens.Conclusions In summary,our findings provide evidences of the grey junglefowl contributing to the genetic diversity of domestic chickens,laying the foundation for a deeper understanding of the genetic composition within domestic chickens,and offering new perspectives on the impact of introgression on domestic chickens.

GS土体硬化剂对车站基坑加固土抗渗性能的影响

基于苏州某地铁车站基坑工程,研究了GS土体硬化剂对不同养护龄期下的粉质黏土和粉砂夹粉土抗渗性能的影响,并进行了现场试验验证。结果表明:掺入GS土体硬化剂能有效提高粉质黏土和粉砂夹粉土的抗渗性能,且随着GS土体硬化剂掺量和养护龄期的增加,提高效果更好;GS土体硬化剂在现场试桩试验中的应用效果较好,可为其在相关工程中的进一步推广应用提供参考。

Case Retrieval Strategy of Turning Process Based on Grey Relational Analysis

To solve the problem of long response time when users obtain suitable cutting parameters through the Internet based platform,a case-based reasoning framework is proposed.Specifically,a Hamming distance and Euclidean distance combined method is designed to measure the similarity of case features which have both numeric and category properties.In addition,AHP(Analytic Hierarchy Process)and entropy weight method are integrated to provide features weight,where both user preferences and comprehensive impact of the index have been concerned.Grey relation analysis is used to obtain the similarity of a new problem and alternative cases.Finally,a platform is also developed on Visual Studio 2015,and a case study is demonstrated to verify the practicality and efficiency of the proposed method.This method can obtain cutting parameters which is suitable without iterative calculation.Compared with the traditional PSO(Particle swarm optimization algorithm)and GA(Genetic algorithm),it can obtain faster response speed.This method can provide ideas for selecting processing parameters in industrial production.While guaranteeing the characteristic information is similar,this approach can select processing parameters which is the most appropriate for the production process and a lot of time can be saved.

Enhancing Hyper-Spectral Image Classification with Reinforcement Learning and Advanced Multi-Objective Binary Grey Wolf Optimization

Hyperspectral(HS)image classification plays a crucial role in numerous areas including remote sensing(RS),agriculture,and the monitoring of the environment.Optimal band selection in HS images is crucial for improving the efficiency and accuracy of image classification.This process involves selecting the most informative spectral bands,which leads to a reduction in data volume.Focusing on these key bands also enhances the accuracy of classification algorithms,as redundant or irrelevant bands,which can introduce noise and lower model performance,are excluded.In this paper,we propose an approach for HS image classification using deep Q learning(DQL)and a novel multi-objective binary grey wolf optimizer(MOBGWO).We investigate the MOBGWO for optimal band selection to further enhance the accuracy of HS image classification.In the suggested MOBGWO,a new sigmoid function is introduced as a transfer function to modify the wolves’position.The primary objective of this classification is to reduce the number of bands while maximizing classification accuracy.To evaluate the effectiveness of our approach,we conducted experiments on publicly available HS image datasets,including Pavia University,Washington Mall,and Indian Pines datasets.We compared the performance of our proposed method with several state-of-the-art deep learning(DL)and machine learning(ML)algorithms,including long short-term memory(LSTM),deep neural network(DNN),recurrent neural network(RNN),support vector machine(SVM),and random forest(RF).Our experimental results demonstrate that the Hybrid MOBGWO-DQL significantly improves classification accuracy compared to traditional optimization and DL techniques.MOBGWO-DQL shows greater accuracy in classifying most categories in both datasets used.For the Indian Pine dataset,the MOBGWO-DQL architecture achieved a kappa coefficient(KC)of 97.68%and an overall accuracy(OA)of 94.32%.This was accompanied by the lowest root mean square error(RMSE)of 0.94,indicating very precise predictions with minimal error.In the case of the Pavia University dataset,the MOBGWO-DQL model demonstrated outstanding performance with the highest KC of 98.72%and an impressive OA of 96.01%.It also recorded the lowest RMSE at 0.63,reinforcing its accuracy in predictions.The results clearly demonstrate that the proposed MOBGWO-DQL architecture not only reaches a highly accurate model more quickly but also maintains superior performance throughout the training process.

Management of Strawberry Grey Mold Disease Using Biocontrol Agents and Plant Extracts

Strawberry (Fragaria × ananassa Duch.) is a significant global soft fruit crop, prized for its nutrient content and pleasant flavor. However, diseases, particularly grey mold caused by Botrytis cinerea Pers. Fr. poses major constraints to strawberry production and productivity. Grey mold severely impacts fruit quality and quantity, diminishing market value. This study evaluated five B. cinerea isolates from various locations in the Ri-Bhoi district of Meghalaya. All isolates were pathogenic, with isolate SGM 2 identified as highly virulent. Host range studies showed the pathogen-producing symptoms in the fava bean pods, marigold, gerbera, and chrysanthemum flowers and in the fava bean, gerbera, and lettuce leaves. In vitro tests revealed that neem extract (15% w/v) achieved the highest mycelial growth inhibition at 76.66%, while black turmeric extract (5% w/v) had the lowest inhibition at 9.62%. Dual culture methods with bio-control agents indicated that Bacillus subtilis recorded the highest mean inhibition at 77.03%, while Pseudomonas fluorescens had the lowest at 20.36% against the two virulent isolates. Pot evaluations demonstrated that B. subtilis resulted in the lowest percent disease index at 20.59%, followed by neem extract at 23.31%, with the highest disease index in the control group at 42.51%. Additionally, B. subtilis significantly improved plant growth, yielding an average of 0.32 kg compared to 0.14 kg in the control. The promising results of B. subtilis and neem leaf extract from this study suggest their potential for eco-friendly managing grey mold in strawberries under field conditions.

Optimization of Agricultural Industrial Structure in Changping District of Beijing Based on Grey Relational Analysis

In the economic development of Beijing,although the share of the total amount of agricultural industry in the overall economy is relatively low,it has an important impact on the daily life of residents,social stability and the development of other industries.Changping District,as an important agricultural production base of Beijing,its agricultural development has an indispensable strategic significance for the stability and growth of the entire regional economy.Therefore,it is very important to study the structure of agricultural industry in Changping District.Based on the detailed analysis of the agricultural industrial structure of Changping District,this paper uses the grey relation theory to analyze the different industries in the agricultural industrial structure of Changping District,including planting,forestry,animal husbandry,fishery and agricultural,forestry,service industries,in order to reveal the impact of these industries on the agricultural industrial structure of Changping District.Through this study,it comes up with specific and feasible suggestions for the optimization of agricultural industrial structure in Changping District,and provides valuable reference for the agricultural development of other areas in Beijing.

Energy-Saving Distributed Flexible Job Shop Scheduling Optimization with Dual Resource Constraints Based on Integrated Q-Learning Multi-Objective Grey Wolf Optimizer

The distributed flexible job shop scheduling problem(DFJSP)has attracted great attention with the growth of the global manufacturing industry.General DFJSP research only considers machine constraints and ignores worker constraints.As one critical factor of production,effective utilization of worker resources can increase productivity.Meanwhile,energy consumption is a growing concern due to the increasingly serious environmental issues.Therefore,the distributed flexible job shop scheduling problem with dual resource constraints(DFJSP-DRC)for minimizing makespan and total energy consumption is studied in this paper.To solve the problem,we present a multi-objective mathematical model for DFJSP-DRC and propose a Q-learning-based multi-objective grey wolf optimizer(Q-MOGWO).In Q-MOGWO,high-quality initial solutions are generated by a hybrid initialization strategy,and an improved active decoding strategy is designed to obtain the scheduling schemes.To further enhance the local search capability and expand the solution space,two wolf predation strategies and three critical factory neighborhood structures based on Q-learning are proposed.These strategies and structures enable Q-MOGWO to explore the solution space more efficiently and thus find better Pareto solutions.The effectiveness of Q-MOGWO in addressing DFJSP-DRC is verified through comparison with four algorithms using 45 instances.The results reveal that Q-MOGWO outperforms comparison algorithms in terms of solution quality.