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The lung cancer incidence and mortality in China have always been high. Moreover, due to the limited level of professional technology, misdiagnosis and missed diagnosis of lung cancer often occur. To improve the accuracy of diagnosis, this paper proposes an interpretable diagnostic method for lung cancer based on Chinese electronic medical records (EMRs). First, to overcome the difficulty in word segmentation of clinical texts in Chinese EMRs, a dictionary construction method is proposed based on the idea of maximal clique, and 730 medical professional terms related to lung diseases are identified. Then, the ProbSparse self‐attention mechanism and self‐attention distilling operation in Informer are used to improve the Bidirectional Encoder Representations from Transformer (BERT) to realize the representation of long clinical texts with lower time complexity and memory consumption. Finally, the convolutional neural network with an attention mechanism is employed to process the representation results to realize the interpretable prediction of lung cancer. This method is applied to the lung cancer diagnosis of inpatients in a tertiary hospital in Hunan Province, obtaining excellent results of about 0.9 for area under the receiver operating characteristic curve (AUROC) and area under the precision‐recall curve (AUPRC). In addition, the results of the comparative analysis with existing dictionaries, word embedding methods and diagnostic methods further confirm the superiority of the proposed method. Specifically, the proposed method improves the precision by at least 6%, the recall by at least 2.6%, the F1 score by at least 5.2%, AUROC by at least 7.3% and AUPRC by at least 7.7% compared with all these state‐of‐the‐art methods. [ABSTRACT FROM AUTHOR]

The stochastic configuration network (SCN), a type of randomized learning algorithm, can solve the infeasible problem in random vector functional link (RVFL) by establishing a supervisory mechanism. The advantages of fast learning, convergence and not easily falling into local optima make SCN popular. However, the prediction effect of SCN is affected by the parameter settings and the nonstationarity of input data. In this paper, a hybrid model based on variational mode decomposition (VMD), improved whale optimization algorithm (IWOA), and SCN is proposed. The SCN will predict relatively stable data after decomposition by VMD, and parameters of SCN are optimized by IWOA. The IWOA diversifies the initial population by employing logistic chaotic map based on bit reversal and improves the search ability by using Lévy flight. The exploration and exploitation of IWOA are superior to those of other optimization algorithms in multiple benchmark functions and CEC2020. Moreover, the proposed model is applied to the prediction of the nonstationary wind speeds in four seasons. We evaluate the performance of the proposed model using four evaluation indicators. The results show that the R2 of the proposed model under four seasons are more than 0.999, and the root mean square error, mean absolute error, and symmetric mean absolute percentage error are less than 0.3, 0.17, and 13%, respectively, which are almost 1/10, 1/10, and 1/4 those of SCN, respectively. [ABSTRACT FROM AUTHOR]

In the multi‐criteria group decision‐making (MCGDM) problems with great uncertainty, making full use of participants' evaluation information could help improve the accuracy and reliability of decision results. Probabilistic linguistic term set (PLTS) is an effective tool to represent qualitative data and can fully express the hesitation and preference of decision makers. Therefore, this paper aims to propose an MCGDM method based on PLTSs. In the proposed method, the projection of PLTSs is explored to measure the distance and angle differences between two objects, and Bayesian best–worst method (Bayesian BWM) is used to determine the aggregated final weights of criteria. Besides, the elimination and choice translating reality III (ELECTRE III) method combined with distillation algorithm deals with the projection of PLTSs to obtain the alternatives' ranking of each decision maker. Then, the weighted convex median voting rule is developed to integrate the rankings results regarding all decision makers, which can solve the conflict of ranking results among experts and ensure that the comprehensive ranking results are reasonable and practical. Finally, a case study of health‐care waste management is designed and comparative analyses are implemented to show the effectiveness and advantages of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, high performance liquid crystal micro‐lens array is realized by adding the High‐Resistance layer and applying the specific driving waveform. Besides, this device is suitable to be utilized in the technique of light field display due to its polarization selectivity and tunability. [ABSTRACT FROM AUTHOR]

Amorphous CoSiB thin films are prepared on Si (111) substrate at different temperatures. A thickness‐induced reversible spin reorientation transition (SRT) of the magnetic direction from in‐plane to out‐of‐plane is observed in the thick films due to the presence of out‐of‐plane anisotropy. Out‐of‐plane anisotropy is abnormally enhanced during the annealing process for films deposited at a low temperature, so the stress relaxation has no influence on out‐of‐plane anisotropy. The thermodynamic magnetization crossover effect from T3/2 to T2 occurs in the thick films due to the itinerant and localized characteristics of the 3d electrons of Co atoms. The temperature‐dependent SRT is found only in the 300‐nm‐thick film as the temperature increases from 5 to 400 K, whereas SRT has previously been shown to occur in the thick glassy films over a large thickness window. The thermodynamic magnetization crossover temperature shifts to a high temperature as the film thickness increases. As the film thickness decreases to 20 nm, the crossover effect disappears, and magnetization varies with temperature following the T2 law in the temperature range from 5 to 400 K. The low‐temperature SRT in the CoSiB alloy is due to the strong spin–orbit coupling, which is responsible for the low‐temperature out‐of‐plane anisotropy. The transition from low to high resistance provides evidence for the presence of localized 3d electrons in Co atoms. [ABSTRACT FROM AUTHOR]

The aim of the present study was to investigate the association of genetic polymorphisms in high mobility group box 1 and 2 ( HMGB1 and HMGB2, respectively) with platinum-based chemotherapy responses in Chinese lung cancer patients. In total, 338 Chinese lung cancer patients (154 responders and 184 non-responders) were recruited to the study. All patients received at least two cycles of first-line platinum-based chemotherapy. Three tagging single nucleotide polymorphisms ( SNPs) of HMGB1 and two tagging SNPs of HMGB2 were detected in patients. We found that rs1412125 and rs2249825 of HMGB1 were significantly associated with the platinum-based chemotherapy response in both recessive and genotypic models. In addition, rs1412125 showed significant association with platinum-based chemotherapy response for the subgroup of patients aged >55 years in additive, recessive and genotypic models. No significant associations were detected between other SNPs and the platinum-based chemotherapy response. The HMGB1 SNPs (rs1412125 and rs2249825) were associated with platinum-based chemotherapy responses in Chinese lung cancer patients. In conclusion, HMGB1 SNPs may serve as potential biomarkers for predicting the efficacy of platinum-based chemotherapy. [ABSTRACT FROM AUTHOR]

The article presents chemical equations related to the article "Biopreparation of an Antiinflammatory Agent, Diarctigenin (I), from Arctiin Isolated from Arctium lappa by Rhizoctonia solani AG-4" by P.-C. Kuo and others, published in the journal "Tetrahedron Letters" in 2013.