中医学视角下城市物质空间的生命要素探析

通过借鉴中医学整体观和生命观的相关理论,从认识城市有机体的生命属性入手,发现并提炼能够产生和传递城市运营所需各种能量的生命要素:廊道和功能体。阐释了其多层级、多性质和多形态的特点,提出了功能体有动力、廊道成系统、敏感点有活力的疏通策略,旨在促进城市各种能量的有机循环,从而维护城市的健康与安全,提高城市生活的效率与质量。     

Stress distribution in thick-walled cylinder due to non-uniform radial pressure on the example of reinforcement corrosion in concrete

This paper presents an analytical solution to the non-uniform pressure on thick-walled cylinder. The formulation is based on the linear elasticity theory (plain strain) and stress function method. As an example, the proposed solution is used to model the stress distribution due to non-uniform steel reinforcement corrosion in concrete. The model is formulated considering different scenarios of corrosion pressure distribution. It is validated against the finite element model for different cases of non-uniform pressure distributions. The results show that the corrosion-induced cracks are likely to start just beyond the anodic zone. This is confirmed by the experimental tests on concrete cylinder exposed to non-uniform accelerated corrosion of steel reinforcement. The model can be effectively used to calculate the distribution of corrosion-induced stresses in concrete.     

The effect of charge on the dihydrogen storage capacity of Sc2–C6H6

The effect of charge on the dihydrogen storage capacity of Sc₂–C₆H₆ has been investigated at B3LYP-D3/6-311G(d,p) level. The neutral system Sc₂–C₆H₆ can store 8H₂ with gravimetric density of 8.76 wt %, and one H₂ dissociates and bonds atomically on the scandium atom. The adsorption of 8H₂ on Sc₂–C₆H₆ is energetically favorable below 155 K. The atom-centered density matrix propagation (ADMP) molecular dynamics simulations show that Sc₂–C₆H₆ can adsorb 3H₂ within 1000 fs at 300K. Compared with Sc₂–C₆H₆, the charged systems can adsorb more hydrogen molecules with higher gravimetric density, and all the H₂ are adsorbed in the molecular form. The gravimetric densities of Sc₂–C₆H₆⁺ and Sc₂–C₆H₆²⁺ are 9.75 and 10.71 wt%. Moreover, the maximum adsorption of charged systems are favorable in wider temperature range. Most importantly, the ADMP-MD simulations indicate that Sc₂–C₆H₆²⁺ can adsorb 6 hydrogen molecules within 1000 fs at 300K. It can be found that the gravimetric density (6.72 wt%) of Sc₂–C₆H₆²⁺ still exceeds the target of US Department of Energy (DOE) under ambient conditions.     

In situ Raman spectroscopic study towards the growth and excellent HER catalysis of Ni/Ni(OH)2 heterostructure

The electrochemical water splitting to produce H₂ in high efficiency with earth-abundant-metal catalysts remains a challenge. Here, we describe a simple “cyclic voltammetry + ageing” protocol at room temperature to activate Ni electrode (AC-Ni/NF) for hydrogen evolution reaction (HER), by which Ni/Ni(OH)₂ heterostructure is formed at the surface. In situ Raman spectroscopy reveals the gradual growth of Ni/Ni(OH)₂ heterostructure during the first 30 min of the aging treatment and combined with polarization measurements, it suggests a positive relation between the Ni/Ni(OH)₂ amount and HER performance of the electrode. The obtained AC-Ni/NF catalyst, with plentiful Ni–Ni(OH)₂ interfaces, exhibits remarkable performance towards HER, with the low overpotential of only 30 mV at a H₂-evolving current density of 10 mA/cm² and 153 mV at 100 mA/cm², as well as a small Tafel slope of 46.8 mV/dec in 1 M KOH electrolyte at ambient temperature. The excellent HER performance of the AC-Ni/NF could be maintained for at least 24 h without obvious decay. Ex situ experiments and in situ electrochemical-Raman spectroscopy along with density functional theory (DFT) calculations reveal that Ni/Ni(OH)₂ heterostructure, although partially reduced, can still persist during HER catalysis and it is the Ni–Ni(OH)₂ interface reducing the energy barrier of H1 adsorption thus promoting the HER performance.     

Functional Dysregulations in CA1 Hippocampal Networks of a 3-Hit Mouse Model of Schizophrenia

For a better translation from treatment designs of schizophrenia to clinical efficiency, there is a crucial need to refine preclinical animal models. In order to consider the multifactorial nature of the disorder, a new mouse model associating three factors (genetic susceptibility—partial deletion of the MAP6 gene, early-life stress—maternal separation, and pharmacological treatment—chronic Δ-9-tetrahydrocannabinol during adolescence) has recently been described. While this model depicts a schizophrenia-like phenotype, the neurobiological correlates remain unknown. Synaptic transmission and functional plasticity of the CA1 hippocampal region of male and female 3-hit mice were therefore investigated using electrophysiological recordings on the hippocampus slice. While basal excitatory transmission remained unaffected, NMDA receptor (NMDAr)-mediated long-term potentiation (LTP) triggered by theta-burst (TBS) but not by high-frequency (HFS) stimulation was impaired in 3-hit mice. Isolated NMDAr activation was not affected or even increased in female 3-hit mice, revealing a sexual dimorphism. Considering that the regulation of LTP is more prone to inhibitory tone if triggered by TBS than by HFS, the weaker potentiation in 3-hit mice suggests a deficiency of intrinsic GABA regulatory mechanisms. Indeed, NMDAr activation was increased by GABA_A receptor blockade in wild-type but not in 3-hit mice. This electrophysiological study highlights dysregulations of functional properties and plasticity in hippocampal networks of 3-hit mice, one of the mechanisms suspected to contribute to the pathophysiology of schizophrenia. It also shows differences between males and females, supporting the sexual dimorphism observed in the disorder. Combined with the previously reported study, the present data reinforce the face validity of the 3-hit model that will help to consider new therapeutic strategies for psychosis.     

基于模糊谱聚类的不确定蛋白质相互作用网络功能模块挖掘

针对谱聚类融合模糊C-means（FCM）聚类的蛋白质相互作用（PPI）网络功能模块挖掘方法准确率不高、执行效率较低和易受假阳性影响的问题，提出一种基于模糊谱聚类的不确定PPI网络功能模块挖掘（FSC-FM）方法。首先，构建一个不确定PPI网络模型，使用边聚集系数给每一条蛋白质交互作用赋予一个存在概率测度，克服假阳性对实验结果的影响；第二，利用基于边聚集系数流行距离（FEC）策略改进谱聚类中的相似度计算，解决谱聚类算法对尺度参数敏感的问题，进而利用谱聚类算法对不确定PPI网络数据进行预处理，降低数据的维数，提高聚类的准确率；第三，设计基于密度的概率中心选取策略（DPCS）解决模糊C-means算法对初始聚类中心和聚类数目敏感的问题，并对预处理后的PPI数据进行FCM聚类，提高聚类的执行效率以及灵敏度；最后，采用改进的边期望稠密度（EED）对挖掘出的蛋白质功能模块进行过滤。在酵母菌DIP数据集上运行各个算法可知，FSC-FM与基于不确定图模型的检测蛋白质复合物（DCU）算法相比，F-measure值提高了27.92%，执行效率提高了27.92%；与在动态蛋白质相互作用网络中识别复合物的方法（CDUN）、演化算法（EA）、医学基因或蛋白质预测算法（MGPPA）相比也有更高的F-measure值和执行效率。实验结果表明，在不确定PPI网络中，FSC-FM适合用于功能模块的挖掘。     

Operational time-series data modeling via LSTM network integrating principal component analysis based on human experience

Today’s information technologies involve increasingly intelligent systems, which come at the cost of increasingly complex equipment. Modern monitoring systems collect multi-measuring-point and long-term data which make equipment health prediction a “big data” problem. It is difficult to extract information from such condition monitoring data to accurately estimate or predict health statuses. Deep learning is a powerful tool for big data processing that is widely utilized in image and speech recognition applications, and can also provide effective predictions in industrial processes. This paper proposes the Long Short-term Memory Integrating Principal Component Analysis based on Human Experience (HEPCA-LSTM), which uses operational time-series data for equipment health prognostics. Principal component analysis based on human experience is first conducted to extract condition parameters from the condition monitoring system. The long short-term memory (LSTM) framework is then constructed to predict the target status. Finally, a dynamic update of the prediction model with incoming data is performed at a certain interval to prevent any model misalignment caused by the drifting of relevant variables. The proposed model is validated on a practical case and found to outperform other prediction methods. It utilizes a powerful deep learning analysis method, the LSTM, to fully process big condition monitoring series data; it effectively extracts the features involved with human experience and takes dynamic updates into consideration.     

Theoretical study of the structural,elastic and thermodynamic properties of chalcopyrite ZnGeP2

The structural, elastic, and thermodynamic properties of ZnGeP₂ with chalcopyrite structure are investigated using the pseudo-potentials plane wave method based on the density functional theory with the generalized gradient approximation. The lattice parameters (a, c and u) are directly calculated and agree well with previous experimental and theoretical results. The obtained negative formation enthalpy shows that ZnGeP₂ crystal has strong structural stability. We have also calculated the bulk modulus B and the elastic parameters (C₁₁, C₁₂, C₁₃, C₃₃, C₄₄, and C₆₆) which have not been measured yet. The accuracy and reliability of the calculated elastic constants of ZnGeP₂ crystal are discussed. In addition, the pressure and temperature dependencies of the lattice parameters, bulk modulus, Debye temperature, Grüneisen parameter, entropy, volume thermal expansion coefficient, and specific heat capacity are obtained in the ranges of 0–20 GPa and 0–1200 K using the quasi-harmonic Debye model. To our knowledge this is the first quantitative theoretical prediction of the thermodynamic properties for ZnGeP₂ compound and still awaits experimental confirmations.