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.     

氮掺杂纳米氧化锌的制备及其光催化去除水中2,4,6-三氯苯酚

以尿素为氮源,用溶胶-凝胶法制备了氮掺杂纳米氧化锌(N-ZnO),用FT-IR、UV-Vis、PL、XRD和XPS对N-ZnO的微观结构和性能进行了表征.以2,4,6-三氯苯酚(TCP)作为目标污染物,研究了N-ZnO在可见光下的催化性能.结果表明:掺杂后,N-ZnO的氧空位缺陷增多,N-ZnO光响应波长向可见光区移动,掺杂摩尔比为0.25时,N-ZnO的光催化性能最好(91;).     

The competitive behavior for O2 and CO2 reaction during char oxy-fuel combustion: effects of temperature and inherent minerals

Journal of Thermal Analysis and Calorimetry - Coal O2/CO2 combustion is a promising carbon capture and storage technology for coal-fired power plant. Char consumption rate prediction is essential...     

GZO/Al复合背电极对非晶硅太阳能电池的影响

随着能源紧缺与环境污染问题的日益严重,太阳能的开发利用越来越受到重视,其中非晶硅薄膜太阳能电池由于其制备工艺简单、价格低廉等优点被广泛地研究.为了使非晶硅薄膜太阳能电池得到更好地利用,提高其转换效率和稳定性显得尤为重要.引入复合背电极是提高非晶硅太阳能电池性能的有效手段,其中对GZO/Al复合背电极的研究还未见报道.在该工作中,利用磁控溅射法在非晶硅电池上制备了GZO/Al复合背电极,研究了复合背电极的制备条件及其对非晶硅太阳能电池性能的影响.结果显示,当GZO层的溅射功率为90 W、Al层的溅射功率为90 W时,具有复合背电极的太阳能电池表现出较好的光电转换性能,其短路电流(ISC)、开路电压(VOC)、填充因子(FF)和电池的光电转换效率(η)分别为8.92 mA、1.55 V、54.48;和7.53;.相较于单层Al背电极的太阳能电池,其光电转换效率大幅提高了47.6;(相对效率).     

The High Energy X-ray telescope (HE) onboard the Insight-HXMT astronomy satellite

The Insight-Hard X-ray Modulation Telescope(Insight-HXMT) is a broadband X-ray and γ-ray(1-3000 ke V) astronomy satellite. One of its three main telescopes is the High Energy X-ray telescope(HE). The main detector plane of HE comprises 18 Na I(Tl)/Cs I(Na) phoswich detectors, where Na I(Tl) is used as the primary detector to measure ~ 20-250 ke V photons incident from the field of view(FOV) defined by collimators, and Cs I(Na) is used as the active shielding detector to Na I(Tl) by pulse shape discrimination. Additionally, Cs I(Na) is used as an omnidirectional γ-ray monitor. The HE collimators have a diverse FOV,i.e. 1.1°×5.7°(15 units), 5.7°×5.7°(2 units), and blocked(1 unit). Therefore, the combined FOV of HE is approximately5.7°×5.7°. Each HE detector has a diameter of 190 mm resulting in a total geometrical area of approximately 5100 cm2, and the energy resolution is ~15% at 60 ke V. For each recorded X-ray event by HE, the timing accuracy is less than 10 μs and the deadtime is less than 10 μs. HE is used for observing spectra and temporal variability of X-ray sources in the 20-250 ke V band either by pointing observations for known sources or scanning observations to unveil new sources. Additionally, HE is used for monitoring the γ-ray burst in 0.2-3 Me V band. This paper not only presents the design and performance of HE instruments but also reports results of the on-ground calibration experiments.     

Recent Advances of Freestanding Cathodes for Li-S Batteries

Lithium-sulfur batteries (LSBs) with high energy density and low cost have been recognized as one of the most promising next-generation energy storage systems. Although it has taken decades of development, the practical application of LSBs has been hindered by several inherent obstacles, particularly the severe shuttle effect and sluggish reaction kinetics in the sulfur cathode. Various strategies have been proposed to address these problems via rational design of electrode materials and configurations. Freestanding sulfur cathode could be a promising strategy to improve the sulfur mass loading at the cathode level and energy density of LSBs. This minireview will briefly summary the recent advances in freestanding cathodes for LSBs. The advantages and disadvantages of various freestanding cathodes are discussed and the prospects for the development of flexible cathodes are envisioned.     

Syntheses,Characterization, and Luminescence Properties of Three Coordination Complexes with Sulfonate-Phenol Anions and Trivalent Metal Ions

Russian Journal of General Chemistry - A dinuclear Tb complex, Tb2(H2L)3(phen)2 (1), and two similar N-donor coordination complexes, Fe(phen)3·HL (2), Fe(bipy)3·HL·5H2O (3) (Na2H2L =...     

Association between the microbiomes of tonsil and saliva samples isolated from pediatric patients subjected to tonsillectomy for the treatment of tonsillar hyperplasia

Oral microbes have the capacity to spread throughout the gastrointestinal system and are strongly associated with multiple diseases. Given that tonsils are located between the oral cavity and the laryngopharynx at the gateway of the alimentary and respiratory tracts, tonsillar tissue may also be affected by microbiota from both the oral cavity (saliva) and the alimentary tract. Here, we analyzed the distribution and association of the microbial communities in the saliva and tonsils of Korean children subjected to tonsillectomy because of tonsil hyperplasia (n = 29). The microbiome profiles of saliva and tonsils were established via 16S rRNA gene sequencing. Based on the alpha diversity indices, the microbial communities of the two groups showed high similarities. According to Spearman’s ranking correlation analysis, the distribution of Treponema, the causative bacterium of periodontitis, in saliva and tonsils was found to have a significant positive correlation. Two representative microbes, Prevotella in saliva and Alloprevotella in tonsils, were negatively correlated, while Treponema 2 showed a strong positive correlation between saliva and tonsils. Taken together, strong similarities in the microbial communities of the tonsils and saliva are evident in terms of diversity and composition. The saliva microbiome is expected to significantly affect the tonsil microbiome. Furthermore, we suggest that our study creates an opportunity for tonsillar microbiome research to facilitate the development of novel microbiome-based therapeutic strategies.Subject terms: Comparative genomics, Metagenomics     

Sentinel-2卫星的多光谱轻量级船舶目标检测算法

近年来深度卷积神经网络在可见光船舶检测方面取得了显著的进展，然而，大多数相关研究是通过改进大型的网络结构来提高检测性能，因此加大了对更高计算机性能的需求。此外，可见光图像难以在云、雾、海杂波、黑夜等复杂场景检测到船舶。针对以上问题，提出了一种融合红（red, R）、绿（green, G）、蓝（blue, B）和近红外（NIR）4个波段光谱信息的由粗到精细的轻量型船舶检测算法。与现有的方法中根据光谱特性利用水体检测算法提取水体区域不同之处是该算法是利用改进的水体检测算法来提取船舶候选区域。为获取更准确的候选区域，对船舶、厚云、薄云、平静海面、杂波海面5种场景中4个波段的像素值进行了统计分析，选取近红外大于阈值作为辅助判断，并以其中心点获取候选区域32×32大小的切片，并对切片进行非极大值抑制，由此获得了船舶粗检测结果。随后构建了轻量级LSGFNet网络对船舶候选区域切片进行精细识别。构建的网络融合了1×1卷积提取的波谱特征与3×3的提取几何特征，为防止光谱特征与几何特征的信息在融合时“信息不流通”，在LSGFNet网络中引入了ShuffleNet中的通道打乱机制，并减小了模型结构，与典型的轻量级网络相比具有更好的效果且模型较小。最后，利用Sentinel-2卫星多光谱10 m分辨率数据构建了512×512大小的1 120组数据进行粗检测，以及32×32大小的6 014组数据进行精细网络训练，其中候选区域粗提取的查全率为98.99%，精细识别网络精确度为96.04%，不同场景下的平均精确度为92.98%。实验表明该算法在抑制云层、海浪杂波等干扰的复杂背景下具有较高的检测效率，且训练时间短、计算机性能需求低。