Improved hemimorphite flotation using xanthate as a collector with S(Ⅱ) and Pb(Ⅱ) activation

The flotation of hemimorphite using the S(Ⅱ)–Pb(Ⅱ)–xanthate process,which includes sulfidization with sodium sulfide,activation by lead cations,and subsequent flotation with xanthate,was investigated.The flotation results indicated that hemimorphite floats when the S(Ⅱ)–Pb(Ⅱ)–xanthate process is used; a maximum recovery of approximately 90% was obtained.Zeta-potential,contact-angle,scanning electron microscopy–energy-dispersive spectrometry(SEM–EDS),and diffuse-reflectance infrared Fourier transform spectroscopy(DRIFTS) measurements were used to characterize the activation products on the hemimorphite surface and their subsequent interaction with sodium butyl xanthate(SBX).The results showed that a Zn S coating formed on the hemimorphite surface after the sample was conditioned in an Na2 S solution.However,the formation of a Zn S coating on the hemimorphite surface did not improve hemimorphite flotation.With the subsequent addition of lead cations,Pb S species formed on the mineral surface.The formation of the Pb S species on the surface of hemimorphite significantly increased the adsorption capacity of SBX,forming lead xanthate(referred to as chemical adsorption) and leading to a substantial improvement in hemimorphite flotation.Our results indicate that the addition of lead cations is a critical step in the successful flotation of hemimorphite using the sulfidization–lead ion activation–xanthate process.     

基于频率的Read Mapping种子选择算法

选择具有最低频率的最优种子是一个复杂的计算问题,往往需要很长时间.提出了一种read的基于频率的合并种子选择算法(FMSS),该算法能够高效地选择接近最优的种子集合,可用于改善现有映射工具的性能.实验对比了平均种子选择方法和当前最优的种子选择策略(OSS,optimal seed solver),结果显示FMSS算法能够用很少的时间代价给出接近OSS的最优种子集合,这表明FMSS算法可集成到现有映射工具中用于处理更大规模的read mapping问题.     

Variable Selection via Generalized SELO-Penalized Cox Regression Models

The seamless-L_0(SELO) penalty is a smooth function that very closely resembles the L_0 penalty, which has been demonstrated theoretically and practically to be effective in nonconvex penalization for variable selection. In this paper, the authors first generalize the SELO penalty to a class of penalties retaining good features of SELO, and then develop variable selection and parameter estimation in Cox models using the proposed generalized SELO(GSELO) penalized log partial likelihood(PPL) approach. The authors show that the GSELO-PPL procedure possesses the oracle property with a diverging number of predictors under certain mild, interpretable regularity conditions. The entire path of GSELO-PPL estimates can be efficiently computed through a smoothing quasi-Newton(SQN) with continuation algorithm. The authors propose a consistent modified BIC(MBIC) tuning parameter selector for GSELO-PPL, and show that under some regularity conditions, the GSELOPPL-MBIC procedure consistently identifies the true model. Simulation studies and real data analysis are conducted to evaluate the finite sample performance of the proposed method.     

Mechanical behavior of a near α titanium alloy under dynamic compression: Characterization and modeling

Dynamic compression tests under strain rates from 870 s^?1 to 2100 s^?1 were conducted for a near α Ti–8Al–1Mo–1V titanium alloy with equiaxed microstructure. Compression behavior, adiabatic shearing and band microstructure were investigated via characterization and calculation. The results demonstrate that all dynamic constitutive curves exhibited obvious stress fluctuation phenomenon with double increase-decrease changing stages at the primary stage of compression. The dislocation multiplication theory can be used to explain this phenomenon. After the stress fluctuation period, work hardening coexisted with the thermal softening, resulting in the slow hardening tendency in constitutive curves. J-C model was utilized to quantify the dynamic constitutive curves. The deviations between the predicted and experimental curves under high strain rates may be attributed to the over-consideration of thermal softening effect in J-C model. Adiabatic shearing band (ASB) began to form under the strain rate of 2100 s^?1. A total shearing strain of 8.1 within ASB achieved in 8.9 μs, corresponding to a local strain rate of about 9.1 × 10⁵ s^?1 and is over 430 times of the macro strain rate. Post annealing was conducted on ASB before EBSD characterization. Due to the static recrystallization during annealing, the α phase within ASB generally presented as ultra-fine grains less than 1 μm in diameter.     

Platelet-derived growth factor receptor beta identifies mesenchymal stem cells with enhanced engraftment to tissue injury and pro-angiogenic property

Mesenchymal stem cells (MSCs) are heterogeneous likely consisting of subpopulations with various therapeutic potentials. Here we attempted to acquire a subset of MSCs with enhanced effect in wound healing. We found that human placental MSCs expressing platelet-derived growth factor (PDGF) receptor (PDGFR)-β exhibited greater proliferation rates and generated more colony-forming unit-fibroblast (CFU-F), compared to PDGFR-β^? MSCs. Notably, PDGFR-β⁺ MSCs expressed higher levels of pro-angiogenic factors such as Ang1, Ang2, VEGF, bFGF and PDGF. When 10⁶ GFP-expressing MSCs were topically applied into excisional wounds in mice, PDGFR-β⁺ MSCs actively incorporated into the wound tissue, resulting in enhanced engraftment (3.92 ± 0.31 × 10⁵ remained in wound by 7 days) and accelerated wound closure; meanwhile, PDGFR-β^? MSCs tended to remain on the top of the wound bed with significantly fewer cells (2.46 ± 0.26 × 10⁵) engrafted into the wound, suggesting enhanced chemotactic migration and engraftment of PDGFR-β⁺ MSCs into the wound. Real-Time PCR and immunostain analyses revealed that the expression of PDGF-B was upregulated after wounding; transwell migration assay showed that PDGFR-β⁺ MSCs migrated eightfold more than PDGFR-β^? MSCs toward PDGF-BB. Intriguingly, PDGFR-β⁺ MSC-treated wounds showed significantly enhanced angiogenesis compared to PDGFR-β^? MSC- or vehicle-treated wounds. Thus, our results indicate that PDGFR-β identifies a subset of MSCs with enhanced chemotactic migration to wound injury and effect in promoting angiogenesis and wound healing, implying a greater therapeutic potential for certain diseases.     

人工智能心理学研究的知识图谱分析

借助CitespaceⅢ对选自WoS的人工智能心理学研究文献进行知识图谱探析,结合自动聚类视图与议题标签展现了人工智能心理学领域的6个知识聚类:#0人工智能解决问题议题;#1人工与人类认知共性议题;#2人工智能学习议题;#3人工智能脑科学议题;#4人工智能环境认知议题;#5人工智能表征议题。在深入探究各聚类的核心与热点知识的基础上分析了人工智能心理学发展的各阶段特征:1.上世纪50年代图灵和米勒等人对机器认知与学习等概念的猜想与初探;2.70-90年代纽厄尔、西蒙和莱尔德等人基于模块记忆与层级分析对人工智能信息处理模型的系统性构建;3.本世纪初基于神经生理学的降维数据认知理论的发展;4.当下人工智能贝叶斯大脑与深度学习理论的兴起。     

基于EPR的供应链治理机制博弈分析

研究了生产者责任延伸(EPR)制度背景下的供应链系统中主体决策影响因素和治理机制的融合问题,基于供应链治理和博弈的理论视角,构造了个体生产者责任(IPR)模式下的非合作博弈模型和集体生产者责任(CPR)模式下的合作博弈模型,分别得出了IPR和CPR模式下企业污染治理技术的最佳决策.研究结果表明,企业的污染治理决策主要取决于企业之间生产技术的差距,以及相互依赖程度.强技术差距和强依赖性更容易导致CPR模式的产生;反之,IPR模式更容易出现在低依赖性和实力相当的企业当中.最后总结了EPR制度下供应链系统动态均衡治理的内部效率机制和外部合法性机制.     

基于学科竞赛培养大学生创新设计和应用实践能力教学改革与研究

开展各类学科竞赛，可以极大地促进对大学生创新能力的培养。竞赛对我国大学教育改革产生了良好的影响，已成为教育发展和改革的一种辅助和促进手段。组织大学生参与各类创新能力培养的各项大赛，是一种培养大学生创新能力非常好的培养方式。不仅可以激励大学生的创新精神、合作精神和培养其创新能力，而且还可以发现许多具有培养前途的拔尖创新人才，激励其脱颖而出。因此，教师加强对本科生创新设计竞赛指导与管理方法研究，对于深化教育改革、推进素质教育、全面提高教学质量以适应21世纪对高素质人才培养的需求是非常有意义的。     

端面顶板冒落高度影响因素 多元线性回归分析

基于数理统计的方法,对影响端面顶板稳定性的多个因素进行了正交试验分析,将顶板冒落高度作为判断指标,得到了各因素的影响程度.影响程度从大到小依次为裂隙发育程度风化岩体强度推进速度端面距=支架初撑力采高.然后,假设端面顶板冒落高度与各影响因素线性相关,采用统计分析软件SPSS对各因素进行多元线性回归分析,结果表明,各因素与顶板冒落高度的线性关系成立,且得到了各因素的回归方程.最后,根据分析结果提出了预防端面顶板冒落的具体措施,为控制端面顶板提供依据.     

从传统徽派家具看当代地域特色生态家具的设计开发

对传统徽派家具的特点进行解读,探讨了地域特色生态家具的发展方向,提出了实现当代地域特色家具的生态设计理念应当采取的途径和策略。