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.     

Fully asynchronous stochastic coordinate descent: a tight lower bound on the parallelism achieving linear speedup

Mathematical Programming - We seek tight bounds on the viable parallelism in asynchronous implementations of coordinate descent that achieves linear speedup. We focus on asynchronous coordinate...     

Close‐Packed Two‐Dimensional Silver Nanoparticle Arrays: Quadrupolar and Dipolar Surface Plasmon Resonance Coupling

Silver nanoparticles (NPs) ranging in size from 40 to 100 nm were prepared in high yield by using an improved seed‐mediated method. The homogeneous Ag NPs were used as building blocks for 2D assembled Ag NP arrays by using an oil/water interface. A close‐packed 2D array of Ag NPs was fabricated by using packing molecules (3‐mercaptopropyltrimethoxysilane) to control the interparticle spacing. The homogeneous 2D Ag NP array exhibited a strong quadrupolar cooperative plasmon mode resonance and a dipolar red‐shift relative to individual Ag NPs suspended in solution. A well‐arranged 2D Ag NP array was embedded in polydimethylsiloxane film and, with biaxial stretching to control the interparticle distance, concomitant variations of the quadrupolar and dipolar couplings were observed. As the interparticle distance increased, the intensity of the quadrupolar cooperative plasmon mode resonance decreased and dipolar coupling completely disappeared. The local electric field of the 2D Ag NP array was calculated by using finite difference time domain simulation and qualitatively showed agreement with the experimental measurements.     

新型4-羟色胺类化合物的合成及生物活性

以4-羟基吲哚为原料,经吲哚环4位乙酰基化、3位亲电取代、酰胺化和还原加氢等反应合成目标化合物7.通过核磁共振氢谱及碳谱对化合物进行结构表征,并对目标化合物进行体外抗氧化生物活性测试.初步生物活性测试结果表明,化合物7a,7b,7c和7d对DPPH·均有很强的清除作用(清除率为85.25%~90.73%),7e,7f,7g,7h作用较差;目标化合物与Vc相比,对·OH的清除作用稍差,最高清除率25.66%(Vc的最高清除率为34.67),但各化合物整体水平相当;在清除O-2·能力上化合物7a,7d,7g,7h最大清除率(分别为19.34,35.35,27.93和31.74)均强于同等浓度的Vc(17.58).     

Asymptotic Behavior of Least Energy Solutions for a Fractional Laplacian Eigenvalue Problem on ℝN

Acta Mathematica Sinica, English Series - We are interested in the existence and asymptotic behavior for the least energy solutions of the following fractional eigenvalue problem $$\left({\rm{P}}...     

紫色球杆菌视紫红质光谱特性的机器学习研究

近年来，机器学习等人工智能技术被应用于蛋白质工程，其在蛋白质结构、功能预测、催化活性等研究中具有独特优势。在未知蛋白质结构的情况下，将蛋白质序列和功能特性与机器学习相结合，基于序列-活性关系（innovative sequence-activity relationship，ISAR）算法，将蛋白质氨基酸序列数字化，用快速傅里叶变换（fast four transform，FFT）进行预处理，再进行偏最小二乘回归建模，可在数据集较少情况下拟合得到最佳模型。通过机器学习对紫色球杆菌视紫红质（gloeobacter violaceus rhodopsin，GR）的突变体蛋白质氨基酸序列与光谱最大吸收波长进行建模，获得了最佳模型。用最佳索引LEVM760106建模得到的确定系数R² 为0.944，均方误差E为11.64。用小波变换进行的预处理，其R² 虽也约为0.944，但E大于11.64，不及FFT进行的预处理。方法较好地解决了蛋白质序列与功能特性之间的数学建模问题，在蛋白质工程中可为预测更优的突变体提供支持。     

Cobalt Based Nanoparticles Embedded Reduced Graphene Oxide Aerogel for Hydrogen Evolution Electrocatalyst

Efficient water electrolysis catalyst is highly demanded for the production of hydrogen as a sustainable energy fuel. It is reported that cobalt derived nanoparticle (CoS₂, CoP, CoS|P) decorated reduced graphene oxide (rGO) composite aerogel catalysts for highly active and reliable hydrogen evolution reaction electrocatalysts. 7 nm level cobalt derived nanoparticles are synthesized over graphene aerogel surfaces with excellent surface coverage and maximal expose of active sites. CoS|P/rGO hybrid aerogel composites show an excellent catalytic activity with overpotential of ≈169 mV at a current density of ≈10 mA cm^?2. Accordingly, efficient charge transfer is attained with Tafel slope of ≈52 mV dec^?1 and a charge transfer resistance (R_ct) of ≈12 Ω. This work suggests a viable route toward ultrasmall, uniform nanoparticles decorated graphene surfaces with well‐controlled chemical compositions, which can be generally useful for various applications commonly requiring large exposure of active surface area as well as robust interparticle charger transfer.