基于GA_XGBoost模型的大学生科研能力预测问题研究

科学评价大学生科研创新能力对我国科研水平的提高具有重要意义.采用机器学习模型来预测大学生科研能力可以起到良好的效果,提出一种GAXGBoost模型来实现对大学生的科研能力预测.此模型是以Xgboost算法为基础,然后充分利用遗传算法的全局搜索能力自动搜索Xgboost最优超参数,避免了人为经验调参不准确的缺陷,最后采用精英选择策略以此确保每一轮都是最佳的进化结果.通过分析表明,所采用的GAXGBoost模型在大学生科研能力预测的结果中具有很高的精度,将此模型与Logistic Regression、Random Forest、SVM等模型进行对比,GAXGBoost模型的预测精度最高.     

The Fifty Percent Machines—A Short History of Influence Machines and an Elementary Theory of Their Efficiency: An Attempt

Presenting the devices invented by Toepler, Holtz, Wimshurst, and Wommelsdorf, the history of the influence machines, the progress made, and the remaining deficits are discussed. The theoretical considerations published in the literature lack generalizable statements on the efficiency. Based on R. W. Pohl's model (1927), an elementary analysis is made, with the result that the upper limit of the theoretically achievable efficiency of influence machines is only 50%.     

Semiconvergence analysis of the randomized row iterative method and its extended variants

The row iterative method is popular in solving the large‐scale ill‐posed problems due to its simplicity and efficiency. In this work we consider the randomized row iterative (RRI) method to tackle this issue. First, we present the semiconvergence analysis of RRI method for the overdetermined and inconsistent system, and derive upper bounds for the noise error propagation in the iteration vectors. To achieve a least squares solution, we then propose an extended version of the RRI (ERRI) method, which in fact can converge in expectation to the solution of the overdetermined or underdetermined, consistent or inconsistent systems. Finally, some numerical examples are given to demonstrate the convergence behaviors of the RRI and ERRI methods for these types of linear system.     

On the numerical solution of ill‐conditioned linear systems by regularization and iteration

We propose to reduce the (spectral) condition number of a given linear system by adding a suitable diagonal matrix to the system matrix, in particular by shifting its spectrum. Iterative procedures are then adopted to recover the solution of the original system. The case of real symmetric positive definite matrices is considered in particular, and several numerical examples are given. This approach has some close relations with Riley's method and with Tikhonov regularization. Moreover, we identify approximately the aforementioned procedure with a true action of preconditioning.     

Quantum algorithm for neighborhood preserving embedding

Neighborhood preserving embedding (NPE) is an important linear dimensionality reduction technique that aims at preserving the local manifold structure. NPE contains three steps, i.e., finding the nearest neighbors of each data point, constructing the weight matrix, and obtaining the transformation matrix. Liang et al. proposed a variational quantum algorithm (VQA) for NPE [Phys. Rev. A 101 032323 (2020)]. The algorithm consists of three quantum sub-algorithms, corresponding to the three steps of NPE, and was expected to have an exponential speedup on the dimensionality n. However, the algorithm has two disadvantages: (i) It is not known how to efficiently obtain the input of the third sub-algorithm from the output of the second one. (ii) Its complexity cannot be rigorously analyzed because the third sub-algorithm in it is a VQA. In this paper, we propose a complete quantum algorithm for NPE, in which we redesign the three sub-algorithms and give a rigorous complexity analysis. It is shown that our algorithm can achieve a polynomial speedup on the number of data points m and an exponential speedup on the dimensionality n under certain conditions over the classical NPE algorithm, and achieve a significant speedup compared to Liang et al.'s algorithm even without considering the complexity of the VQA.     

The impact of insecticides containing deltamethrin and cyfluthrin on the composition of surface compounds in the larvae,females and males of Tenebrio molitor

This paper presents the effect of insecticides on the composition of the surface compounds of one of the most harmful insects, Tenebrio molitor, by analysis using GC–MS. As a result of the use of insecticides, the composition of the chemical compounds on the surface of insects changes, depending on the insecticides used. The most numerous groups of the marked compounds were fatty acids, alkanes, esters and sterols. The content of the identified compounds in the larvae increased at both 24 and 48 h after the application of insecticides, in comparison with the control samples. The content of identified compounds in the samples taken from the females increased 24, 48 and 72 h after the application of insecticides in comparison with the control samples. By contrast, in samples prepared from males, the content of identified compounds decreased 24 h after the application of insecticides, compared with the control samples. The highest content of chemical compounds was for fatty acids and alkanes after the use of insecticides. The content of fatty acids after the application of the insecticide with deltamethrin was 62.1 ± 3.3–466.9 ± 5.9 μg/g, and after the application of the insecticide with cyfluthrin was 49.9 ± 1.9–458.3 ± 4.2 μg/g. However, the content of alkanes after the use of deltamethrin was 115.6 ± 4.2–4672.0 ± 32.1 μg/g, and after the use of cyfluthrin was 189.4 ± 3.8–3975.0 ± 10.2 μg/g.     

基于视觉辐条图案识别方法的蓝宝石引晶机制研究

工业生产蓝宝石晶体过程中,引晶步骤有着至关重要的地位。引晶必须在温度梯度较小,温度分布趋于稳定的条件下进行。目前,工业生产蓝宝石主要依靠人工经验操控籽晶杆实现引晶操作,但是人工引晶操作的准确性不高会导致成品品质不佳、资源浪费。为此,本文提出一种基于蓝宝石视觉辐条图案识别方法来检测蓝宝石熔体状态自由液面状态,从而实现一种高效率引晶的机制。此方法利用经典骨架化算法细化辐条图案,Harris算子实现特征信息的提取,提取的特征信息放入运动轨迹模型中判断熔体稳定性,分析液面温度分布稳定性从而实现引晶。结果表明,此算法具有有效性,蓝宝石晶体引晶效率大大提高,生产出的成品良率也有提升,可有效指导蓝宝石的工业生产。     

LC-MS-based multi-omics analysis of brain tissue for the evaluation of the anti-ischemic stroke potential of Tribulus terrestris L. fruit extract in MCAO rats

This study aimed to investigate the chemical composition of Tribulus terrestris L. fruit (TT) extract named TT15 and its protective effect against ischemic stroke (IS) as well as corresponding mechanisms. The chemical composition of TT15 was analyzed by liquid chromatography-mass spectrometry (LC-MS), and the compound identification was conducted via searching the in-house database. The LC-MS-based multi-omics approach was applied to search the differential metabolites and differential proteins in rat brain tissue and to explore the biomarker and molecular mechanism of TT15 against middle cerebral artery occlusion (MCAO). A total of 20 compounds were identified from TT15, mainly including alkaloids, flavonoids, phenols, quinones, and esters. These 20 compounds significantly affected the metabolism of 44 metabolites and the expression of 51 proteins. Joint pathway analysis showed that these metabolites and proteins were mainly involved in the response to elevated platelet cytosolic Ca²⁺ and platelet activation, which inferred that TT15 may exert a protective effect against cerebral ischemic injury via regulating platelet function. This study provides useful information for further exploration of the mechanisms of TT extract against IS.