重新找回人工智能的可解释性

针对深度神经网络AI研究的可解释性瓶颈，指出刚性逻辑（数理形式逻辑）和二值神经元等价，二值神经网络可转换成逻辑表达式，有强可解释性。深度神经网络一味增加中间层数来拟合大数据，没有适时通过抽象把最小粒度的数据（原子）变成粒度较大的知识（分子），再把较小粒度的知识变成较大粒度的知识，把原有的强可解释性淹没在中间层次的汪洋大海中。要支持多粒度的知识处理，需把刚性逻辑扩张为柔性命题逻辑（命题级数理辩证逻辑），把二值神经元扩张为柔性神经元，才能保持强可解释性。本文详细介绍了从刚性逻辑到柔性逻辑的扩张过程和成果，最后介绍了它们在AI研究中的应用，这是重新找回AI研究强可解释性的最佳途径。     

Homogeneous and Universal Detection of Various Targets with a Dual-Step Transduced Toehold Switch Sensor

Toehold switch sensors represent a class of new advances that allow specific targets to trigger in situ expression of a protein reporter. Although they offer unique advantages of a label-free nature and high portability, they generally require repeated sequence design, high expenditure, and laborious optimization of toehold switch sequences according to different targets. To simplify the sensing process further and to improve its practicability, we innovatively introduce a dual-step pre-transduction upon traditional toehold switch sensor. Through two successive toehold-mediated strand-displacement reactions that are initiated, respectively, by a linear and an associative trigger, different DNAs, RNAs, or ligands of functional nucleic acids can be generally transduced into the input of one high-performance toehold switch sensor. This advance greatly increases the target range. Furthermore, the whole process is signal-on, homogeneous, and free of any requirements for complicated operations such as probe labeling, separation, and reconstruction of the toehold switch, being promising and practical even in portable or point-of-care assays.     

Mixture ratio modeling of dynamic systems

Any knowledge extraction relies (possibly implicitly) on a hypothesis about the modelled-data dependence. The extracted knowledge ultimately serves to a decision-making (DM). DM always faces uncertainty and this makes probabilistic modelling adequate. The inspected black-box modeling deals with “universal” approximators of the relevant probabilistic model. Finite mixtures with components in the exponential family are often exploited. Their attractiveness stems from their flexibility, the cluster interpretability of components and the existence of algorithms for processing high-dimensional data streams. They are even used in dynamic cases with mutually dependent data records while regression and auto-regression mixture components serve to the dependence modeling. These dynamic models, however, mostly assume data-independent component weights, that is, memoryless transitions between dynamic mixture components. Such mixtures are not universal approximators of dynamic probabilistic models. Formally, this follows from the fact that the set of finite probabilistic mixtures is not closed with respect to the conditioning, which is the key estimation and predictive operation. The paper overcomes this drawback by using ratios of finite mixtures as universally approximating dynamic parametric models. The paper motivates them, elaborates their approximate Bayesian recursive estimation and reveals their application potential.     

一种精确测量ASTM标准圆形拉伸试样锥度的方法

介绍了ASTM标准中圆形拉伸试样主要部位的尺寸与要求。采用国产万能工具显微镜-投影法对试样在平行长度部位的锥度进行了测量。该方法简便易行,结果准确可靠,满足了标准要求,同时发挥了老设备的作用,保证了试样的加工精度。     

论万向节式托辊组的结构及性能缺陷

托辊是确保带式输送机平稳运行的关键部件 ,其结构虽然简单。但若干年来 ,人们对它的研究却从未间断过 ,其工作性能和可靠性得到不断提高。万向节式托辊是一种新型托辊 ,但作者从运动学、制造工艺学等角度分析了万向节式托辊的工作特性及其弊端 ,对正确选用带式输送机托辊具有启发性     

n次回旋线的平行线方程及其特性分析

推导了n次回旋线的平行线方程 ,分析了n次回旋线的平行线与n次回旋线的关系 ,提出了可以将n次回旋线的平行线看成是通用n次回旋线 ,证明了通用n次回旋线的圆曲线内移值和切线增量与n次回旋线的圆曲线内移值和切线增量相等。     

钢骨混凝土柱正截面承载力计算的叠加方法

根据塑性理论下限定理,对于给定的轴向力,由平衡条件任意分配钢骨部分和钢筋混凝土部分承担的轴力,并分别求得相应各部分的受弯承载力,两部分受弯承载力之和的最大值,即为钢骨混凝土柱在该轴力下的受弯承载力。本文针对工程中常用的对称配筋形式,推导出解析解,解决了直接采用一般叠加方法计算钢骨混凝土柱正截面承载力反复试算的困难,讨论了钢骨部分和钢筋混凝土部分所承担轴力比例的影响因素,并在大量计算分析的基础上,提出了简化的计算方法,为一般叠加方法的工程应用提供了理论基础和简捷的计算方法。     

信息认知逻辑及理论

本文主要探讨信息论跨学科发展的基本问题、理论和方法。通过分析Shannon测度,得出:‘划分’是获取信息的依据和根本方法。利用连续划分由离散信源熵推导连续信源熵。可消除logΔ→∞的矛盾。通过讨论模糊划分,得到划分的信息客观度和信息散失度;定量解决了正确选择‘划分’的问题。针对Shannon信源和划分的缺陷,本文提出了普适划分。从而可以认知信源输出的语法信息和语义识别信息;并且证明:Shannon信息是后者的近似。对先验知识不足的信源,用灰色信源描述。灰熵、灰信息作为熵和信息的估计;并用感知度δ_k定量描述了它们的接近程度,     

清华校训与通才教育

当年清华国学研究院的梁启超先生提出以“自强不息 ,厚德载物”作为清华校训。从此 ,这一校训激励了一代又一代清华人自强不息 ,朝着品学兼优的方向发展。在“通识为本 ,专识为末”的通才教育思想指导下 ,清华为国家造就了一大批栋梁之才。今天我们通过对清华校训及清华教育宗旨的进一步领悟 ,来探讨通才教育的真谛 ,探讨今天大学及大学教育的真正意义 ,无疑有助于我们搞好高等教育事业