Analysis on Explanation Effect of the European Numerical Prediction on Temperature

[Objective] The research aimed to analyze explanation effect of the European numerical prediction on temperature. [Method] Based on CMSVM regression method, by using 850 hPa grid point data of the European numerical prediction from 2003 to 2009 and actual data of the maximum and minimum temperatures at 8 automatic stations in Qingyang City, prediction model of the temperature was established, and running effect of the business from 2008 to 2010 was tested and evaluated. [Result] The method had very good guidance role in real-time business running of the temperature prediction. Test and evaluation found that as forecast time prolonged, prediction accuracies of the maximum and minimum temperatures declined. When temperature anomaly was higher (actual temperature was higher than historical mean), prediction accuracy increased. Influence of the European numerical prediction was bigger. [Conclusion] Compared with other methods, operation of the prediction method was convenient, modeling was automatic, running time was short, system was stable, and prediction accuracy was high. It was suitable for implementing of the explanation work for numerical prediction product at meteorological station.

Theoretical Explanation and Improvement to the Flare Model of Lithography Based on the Kirk Test

The Kirk test has good precision for measuring stray light in optical lithography and is the usual method of measuring stray light.However,Kirk did not provide a theoretical explanation to his simulation model.We attempt to give Kirk's model a kind of theoretical explanation and a little improvement based on the model of point spread function of scattering and the theory of statistical optics.It is indicated by simulation that the improved model fits Kirk's measurement data better.

Alternative kind of hydrogen atoms as a possible explanation for the latest puzzling observation of the 21 cm radio line from the early Universe

There is a puzzling astrophysical result concerning the latest observation of the absorption profile of the redshifted radio line 21 cm from the early Universe(as described in Bowman et al.). The amplitude of the profile was more than a factor of two greater than the largest predictions. This could mean that the primordial hydrogen gas was much cooler than expected. Some explanations in the literature suggested a possible cooling of baryons either by unspecified dark matter particles or by some exotic dark matter particles with a charge a million times smaller than the electron charge. Other explanations required an additional radio background. In the present paper, we entertain a possible different explanation for the above puzzling observational result: the explanation is based on the alternative kind of hydrogen atoms(AKHA),whose existence was previously demonstrated theoretically, as well as by the analysis of atomic experiments. Namely, the AKHA are expected to decouple from the cosmic microwave background(CMB) much earlier(in the course of the Universe expansion) than usual hydrogen atoms, so that the AKHA temperature is significantly lower than that of usual hydrogen atoms. This seems to lower the excitation(spin) temperature of the hyperfine doublet(responsible for the 21 cm line) sufficiently enough for explaining the above puzzling observational result. This possible explanation appears to be more specific and natural than the previous possible explanations. Further observational studies of the redshifted 21 cm radio line from the early Universe could help to verify which explanation is the most relevant.

Regulation on the Protection of Fossils Issued by the State Council of the People's Republic of China:Scientists' Researches Protected Legally—Further Explanation

With large-scale engineering projects being carried out in China, a large number of fossil localities have been discovered and excavated by responsible agencies, but still some important fossils of great value have been removed and smuggled into foreign countries. In the last three years, more than 1345 fossil specimens have been intercepted by Customs in Shenzhen, Shanghai, Tianjin, Beijing and elsewhere, and more than 5000 fossils, most of which are listed as key fossils,

Parallel Vision ■ Image Synthesis/Augmentation

Dear Editor,Scene understanding is an essential task in computer vision.The ultimate objective of scene understanding is to instruct computers to understand and reason about the scenes as humans do.Parallel vision is a research framework that unifies the explanation and perception of dynamic and complex scenes.

A theoretical explanation of the decays of Majorana oscillations

Majorana zero modes in the hybrid semiconductor-superconductornanowire is one of the promising candidates for topologicalquantum computing. Recently, in nanowires with a superconductingisland, the signature of Majorana zero modescan be revealed as a subgap state whose energy oscillatesaround zero in magnetic field. This oscillation was interpretedas overlapping Majoranas. However, the oscillation amplitudeeither dies away after an overshoot or decays, sharply oppositeto the theoretically predicted enhanced oscillations for Majoranabound states, as the magnetic field increases. Several theoreticalstudies have tried to address this discrepancy, but arepartially successful. This discrepancy has raised the concernson the conclusive identification of Majorana bound states, andhas even endangered the scheme of Majorana qubits basedon the nanowires.

THEORETICAL EXPLANATION OF SPIN REORIENTATION IN DyTiFe_(11) COMPOUND

DyTiFe_(11) compound is a ferromagnetic substance.It has tetragonal body-centered ThMn_(12)-type crystallographic structure.At room temperature,the easy magnetization direction is the c-axis.A spin reorientation begins to appear at about 175K.The contribution of Fe sublattice to magnetocrystalline anisotropy was determined by experiments and that of Dy sublattice was obtained by using single ion model calculation.Results show that the spin reorientation arises from the competition of anisotropy between Fe and Dy sublattices.

An Explanation for the Undetection of Radio Pulsar in Supernova 1987A

Supernova 1987 A is a core collapse supernova in the Large Magellanic Cloud, inside which the product is most likely a neutron star. Despite the most sensitive available detection instruments from radio to γ-ray wavebands being exploited in the pass thirty years, there have not yet been any pulse signals detected. By considering the density of the medium plasma in the remnant of 1987 A, we find that the plasma cut-off frequency is approximately7 GHz, a value higher than the conventional observational waveband of radio pulsars. As derived, with the expansion of the supernova remnant, the radio signal will be detected in 2073 A.D. at 3 GHz.

Explaining How： The Intelligibility of Mechanical Explanations in Boyle

In this paper I examine the following claims by William Eaton in his monograph Boyle on Fire： （i） that Boyle＇s religious convictions led him to believe that the world was not completely explicable, and this shows that there is a shortcoming in the power of mechanical explanations; （ii） that mechanical explanations offer only sufficient, not necessary explanations, and this too was taken by Boyle to be a limit in the explanatory power of mechanical explanations; （iii） that the mature Boyle thought that there could be more intelligible explanatory models than mechanism; and （iv） that what Boyle says at any point in his career is incompatible with the statement of Maria Boas-Hall, i.e., that the mechanical hypothesis can explicate all natural phenomena. Since all four of these claims are part of Eaton＇s developmental argument, my rejection of them will not only show how the particular developmental story Eaton diagnoses is inaccurate, but will also explain what limits there actually are in Boyle＇s account of the intelligibility of mechanical explanations. My account will also show why important philosophers like Locke and Leibniz should be interested in Boyle＇s philosophical work.

On the effects of contextualized explanation and Ebbinghaus Forgetting Curve on the teaching and learning of English vocabulary

This paper reports the outcomes of three vocabulary tests taken by 71 second-year undergraduates, discusses the possible effects of contextualized explanation of new words and Ebbinghaus Forgetting Curve on the vocabulary teaching and learning. The authors find that in a short duration there is a significant difference between the effect of bilingual （English ＆ Chinese） explanation and that of monolingual （Chinese） explanation on the students＇ recognition of English new words.

Effects of Explanation Type on Consumers' Perceived Usefulness of Online Reviews and Their Boundary Conditions

In making purchasing decisions, consumers look to online reviews posted by others who have used or experienced the product/service. Most existing studies on online reviews only focused on their content without addressing how their explanation type influences purchasing decisions, not to mention the boundary conditions for such effects. Based on three experimental studies, this paper examines how explanation type affects the perceived usefulness of online reviews and purchasing decisions, and discusses the boundary conditions for such effects. Our findings show that positive explanation type has a positive effect on the perceived usefulness of online reviews, while negative explanation has an insignificant impact. For search products, there is a positive correlation between the online reviews of explained actions and the perceived usefulness of consumer reviews. For experience products, there is a positive correlation between the online reviews of explained reactions and the perceived usefulness of consumer reviews. Further research found that temporal distance may moderate the effects of explanation type and product type on the perceived usefulness of online reviews. This study also provides a new approach for research on the word-of-mouth(WOM) with meaningful implications for e-commerce firms.

A Study on the Explanation of Conceptual Metaphor in English Business News

In English business news discourses, there are numerous financial words or terms which are quite difficult for readers to under-stand, especially those ones built on the basis of metaphorical mechanism. Conceptual Metaphor has a strong power to explain the cor-rect meaning of these words with their specific types of metaphors. Through the explanation of the meaning construction of the metaphori-cal words, it can be a great help for the news readers to master the accurate and deep-seated messages in the discourse. Simultaneously,it gives the reader an insight into the English culture in order to grasp the international economic trends and makes them accomplishcross-cultural communication task with ease.

Review on Gesture and Speech in the Vocabulary Explanations of One ESL Teacher： A Microanalytic Inquiry＂ by Anne Lazaraton

This paper takes a microanalytic perspective on the speech and gestures used by one teacher of ESL （English as a Second Language） in an intensive English program classroom. Videotaped excerpts from her intermediate-level grammar course were transcribed to represent the speech, gesture and other non-verbal behavior that accompanied unplanned explanations of vocabulary that arose during three focus-on-form lessons. The gesture classification system of McNeill （1992）, which delineates different types of hand movements （iconics metaphorics, deictics, beats）, was used to understand the role the gestures played in these explanations. Results suggest that gestures and other non-verbal behavior are forms of input to classroom second language learners that must be considered a salient factor in classroom-based SLA （Second Language Acquisition） research

Detailed explanation of textile and apparel foreign trade in the first 7 months

Trade data In July,the total import and export value of national trade in goods was USD 412.93 billion,an increase of 3.4%year-on-year(the same below),of which exports were USD 237.63 billion,an increase of 7.2%,and imports were USD 175.3 billion,a decrease of 1.4%.The trade surplus for the month was USD 62.33 billion.From January to July,the total import and export value was USD 244.263 billion,a year-on-year decrease of 4.8%,of which exports were USD 133.638 billion,a decrease of 4.1%,imports were USD 110.625 billion,a decrease of 75.7%,and a cumulative surplus of USD 230.13 billion was achieved.

Study on the facial spectrum and color characteristics of patients with essential hypertension

Objective To investigate the facial spectrum and color characteristics of patients with essen-tial hypertension post administering antihypertensive drugs,establish a classification and evaluation model based on the facial colors of the enrolled patients,and perform in-depth analysis on the important characteristics of their facial spectrum.Methods From September 3,2018,to March 23,2024,participants with essential hyperten-sion(receiving antihypertensive medication treatment,hypertension group)and normal blood pressure(control group)were recruited from the Cardiology Department of Shanghai Hospital of Traditional Chinese Medicine,the Coronary Care Unit of Shanghai Tenth People's Hospital,the Physical Examination Center of Shuguang Hospital Affiliated to Shanghai Uni-versity of Traditional Chinese Medicine,and the Gaohang Community Health Service Center.This study employed the propensity score matching(PSM)method to reduce study partici-pants selection bias.Spectral information in the facial visible light spectrum of the subjects was collected using a flame spectrometer,and the spectral chromaticity values were calculat-ed using the equal-interval wavelength method.The study analyzed the differences in spec-tral reflectance across various facial regions,including the entire face,forehead,glabella,nose,jaw,left and right zygomatic regions,left and right cheek regions as well as differences in parameters within the Lab color space between the two subject groups.Feature selection was conducted using least absolute shrinkage and selection operator(LASSO)regression,fol-lowed by the application of various machine learning algorithms,including logistic regres-sion(LR),support vector machine(SVM),random forest(RF),Naïve Bayes(NB),and eX-treme Gradient Boosting(XGB).The reduced-dimensional dataset was split in a 7:3 ratio to establish a classification and assessment model for facial coloration related to primary hyper-tension.Additionally,model fusion techniques were applied to enhance the predictive power.The performance of the models was evaluated using metrics including the area under the curve(AUC)and accuracy.Shapley Additive exPlanations(SHAP)was used to interpret the outcomes of the models.Results A total of 114 participants were included in both hypertension and control groups.Reflectance analysis across the entire face and eight predefined areas revealed that the hypertensive group exhibited significantly higher reflectance of corresponding color light in the blue-violet region(P<0.05)and a lower reflectance in the red region(P<0.05)compared with control group.Analysis of Lab color space parameters across the entire face and eight predefined areas showed that hypertensive group had significantly lower a and b values than control group(P<0.05).LASSO regression analysis identified a total of 18 facial color features that were highly correlated with hypertension,including the a values of the chin and the right cheek,the reflectance at 380 nm and at 780 nm of the forehead.The results of the multi-mod-el classification showed that the RF classification model was the most effective,with an AUC of 0.74 and an accuracy of 0.77.The combined model of RF+LR+SVM outperformed a single model in their classification performance,achieving an AUC of 0.80 and an accuracy of 0.76.SHAP model visualization results indicated that the top three contributors to ideal prediction results based on the characteristics from the facial spectrum were the reflectance at 380 nm across the entire face and of the nose as well as the a value of the chin.Conclusion Within the same age group,patients with essential hypertension exhibited signif-icant and regular changes in facial color and facial spectral reflectance parameters after the administration of antihypertensive drugs.Furthermore,facial reflectance indicators,such as the overall reflectance at 380 nm and the a value of the chin,could offer valuable references for clinically assessing the drug efficacy and health status of patients with essential hyperten-sion.

Explainable machine learning model for predicting molten steel temperature in the LF refining process

Accurate prediction of molten steel temperature in the ladle furnace(LF)refining process has an important influence on the quality of molten steel and the control of steelmaking cost.Extensive research on establishing models to predict molten steel temperature has been conducted.However,most researchers focus solely on improving the accuracy of the model,neglecting its explainability.The present study aims to develop a high-precision and explainable model with improved reliability and transparency.The eXtreme gradient boosting(XGBoost)and light gradient boosting machine(LGBM)were utilized,along with bayesian optimization and grey wolf optimiz-ation(GWO),to establish the prediction model.Different performance evaluation metrics and graphical representations were applied to compare the optimal XGBoost and LGBM models obtained through varying hyperparameter optimization methods with the other models.The findings indicated that the GWO-LGBM model outperformed other methods in predicting molten steel temperature,with a high pre-diction accuracy of 89.35%within the error range of±5°C.The model’s learning/decision process was revealed,and the influence degree of different variables on the molten steel temperature was clarified using the tree structure visualization and SHapley Additive exPlana-tions(SHAP)analysis.Consequently,the explainability of the optimal GWO-LGBM model was enhanced,providing reliable support for prediction results.

基于集成因子优选算法的面板堆石坝变形预测模型

面板堆石坝变形主要受外部荷载和内部材料蠕变影响,而影响因子过多会造成特征冗余,引起预测精度过拟合问题;因子过少导致信息表达不全,造成预测效果差,模型泛化能力不足等问题.因此构建涵盖面广,可解释性强的因子集并从中优选格外重要.针对上述问题,文中提出基于集成因子优选算法的面板堆石坝变形预测模型,使用ReliefF与沙普利加性解释(SHAP)算法通过权重集成获得因子贡献值排序,再分析因子累计贡献率差量阈值剔除非关键因子,获得关键因子.以新疆某混凝土面板堆石坝为例,以特征缩减率FRR、归一化平均绝对百分比误差nMAPE、平均绝对误差MAE、均方误差MSE以及决定系数R^(2)为评价指标,试验结果表明文中提出的算法面对不同的预测模型都可准确地获得最佳因子,有效地提升了预测精度.相对于传统因子优选算法适应性更强,预测能力提升最显著,解决了影响因子冗余或者欠缺带来的预测能力较低的问题,提高了模型的泛化能力,为大坝安全监测研究提供了行之有效的因子优选方法.

基于Shapley additive explanations(SHAP)分析乳腺X线检查假阴性乳腺癌的特征

目的:基于Shapley additive explanations(SHAP)分析乳腺X线摄影(MG)检查假阴性乳腺癌的特征。方法:回顾性收集我院2018年1月—2022年5月首诊乳腺癌患者,评估临床病理和影像学表现。通过logistic回归分析确定MG假阴性乳腺癌的独立危险因素。应用SHAP分析各独立危险因素的贡献价值。结果:1505个病灶纳入研究,MG假阴性乳腺癌373个。较小的病灶、致密或不均匀致密的MG密度、无可疑钙化、非肿块样强化(NME)、原位癌和腋窝淋巴结阴性与MG假阴性乳腺癌独立相关,上述参数构建的联合模型具有良好的预测效能(AUC=0.871)。根据SHAP分析,病灶大小、MG密度和病灶MRI强化类型是导致MG假阴性的主要因素;钙化状态、病理类型和腋窝淋巴结状态是重要补充。结论:MG假阴性乳腺癌具有一定的特征,此类患者需补充乳腺MRI检查以提高癌灶的检出率。

基于无人机图像和SHAP特征筛选的小麦田间产量预测方法研究

为了探寻适宜的小麦产量预测模型并提高其精度,从冬小麦灌浆期的无人机多光谱和RGB图像中提取了14种光谱参数和28种形态参数作为特征变量,利用线性回归、随机森林、神经网络等10种机器学习方法构建小麦田间产量预测模型,并比较了模型间预测能力的差异;同时,引入机器学习事后可解释性方法SHAP对输入的特征变量进行重要性分析和筛选,了解其提高模型预测能力的效果。结果表明:(1)10种机器学习模型中,误差逆传播神经网络BPNN的产量预测表现最好(r^(2)=0.826,RMSE=0.094 t·hm^(-2));(2)根据SHAP确定的特征变量重要性排序,花青素反射指数ARI和三维冠层体积Volume对于预测结果的影响最大,占全部特征重要性总和的45.48%;(3)经过SHAP特征筛选后,确定了在BPNN产量预测模型上表现最优的9个特征变量,其预测结果r^(2)为0.865,RMSE为0.075 t·hm^(-2),比使用全特征的BPNN和事前Pearson相关性分析方法在预测精度上均有提升。因此,在优选产量预测模型基础上,可采用SHAP机制对特征变量的重要性进行筛选和分析,以此进一步提高田间小麦产量预测精度。