Multi‐Responsive Polypeptidosome: Characterization,Morphology Transformation,and Triggered Drug Delivery

The biodegradable polymeric nanomedicines that may be integrated with multi‐stimuli‐sensitivity to achieve triggered or on‐demand drug release kinetics are challenging for polymer therapeutics and drug delivery systems. By controlling the structure transformation of one polypeptide‐b‐PEO copolymer, a novel multi‐responsive polypeptide‐based vesicle (polypeptidosome) presents the combined sensitivity of multiple physiological and clinic‐related stimuli, and both morphology and size of the polypeptidosome are changed during the triggered process. The designer polypeptide has unique structures composed of 1) light‐responsive o‐nitrobenzyl groups, 2) oxidizable thioether linkers, 3) photo‐caged redox thiol groups on parent poly(L‐cysteine), and 4) tunable conformation, which enable the polypeptidosome to have a peculiar multi‐response. The anticancer drug doxorubicin can be released in a controlled or on–off manner. The combination stimuli of UV irradiation and H₂O₂ oxidation induces a large effect and a lower IC₅₀ of 3.80 μg doxorubicin (DOX) equiv/mL compared to 5.28 μg DOX equiv/mL of individual H₂O₂ trigger.

     

Bioreducible Nanocapsules Prepared from the Self‐assembly of Branched Polymer in Nanodroplet

Though great attention has been paid in constructing well‐defined nano‐structures via the self‐assembly of amphiphilic macromolecules, the self‐assembly of non‐amphiphilic macromolecules in nanodroplet has drawn less attention up to now. Recently, we prepared a temperature‐responsive PEG‐based branched polymer with disulfide bonds in its backbone via reversible addition–fragmentation chain transfer (RAFT) polymerization of 2‐(2‐methoxyethoxy) ethyl methacrylate, oligo(ethylene glycol) methacrylate, and N,N′‐cystamine bisacrylamide. Subsequently, we loaded the branched polymer into nanodroplets, and have found that the self‐assembly behaviors of this branched poly­mer in the nanodroplet are different from those in common solution. Bioreducible nanocapsules with tunable size can easily formed in nanodroplet even at high concentration.

     

Sudden Change of Quantum Discord in Qutrit-Qutrit System Under Depolarising Noise

The effects of decoherence on quantum discord of two-qutrit system under the influence of multilocal, collective and global depolarising noises are investigated. Sudden change of quantum discord with the decoherence parameter and the initial state parameter occurs for the qutrits being coupled to multilocal or global depolarising noises. On the other hand, decoherence cannot induce sudden change of quantum discord when the system is collectively coupled to the depolarising noise. In addition, the local unitary transformation can alter the region in which the phenomenon of sudden change exists.     

Wood species identification using improved active shape model

In this paper, we propose a robust wood species identification scheme by using color wood surface images. First, a novel wood image acquirement system is devised, and the wood color image is converted into a V₁V₂I color-base image. Second, the corresponding grey histograms for V₁ and V₂ are established. Third, an improved active shape model is used to fulfill the curve deformation of the histogram curve of the standard specimen. This active shape model will then converge to the histogram curve of the test specimen. Finally, wood recognition is performed by comparing the initial and final active shape models with the histogram curve of the test specimen. We have experimentally proved that this scheme improves the mean recognition accuracy to approximately 90% for 5 wood species and that it can also be applied to the Gaussian noisy images. Moreover, the recognition accuracy can be further improved by combining this scheme with the texture feature recognition.     

静电场中电场强度的数值意义

“近场强远场弱”是静电场的普遍特点,宏观带电体的静电场是点电荷电场叠加的结果.本文以静电场中两个实际的电场强度问题为例,用相对数值比较了电荷分布对电场强度的贡献,阐述电场强度“近场强远场弱”的数值意义.     

Network dynamics and its relationships to topology and coupling structure in excitable complex networks

All dynamic complex networks have two important aspects, pattern dynamics and network topology. Discovering different types of pattern dynamics and exploring how these dynamics depend or/network topologies are tasks of both great theoretical importance and broad practical significance. In this paper we study the oscillatory behaviors of excitable complex networks （ECNs） and find some interesting dynamic behaviors of ECNs in oscillatory probability, the multiplicity of oscillatory attractors, period distribution, and different types of oscillatory patterns （e.g., periodic, quasiperiodic, and chaotic）. In these aspects, we further explore strikingly sharp differences among network dynamics induced by different topologies （random or scale-free topologies） and different interaction structures （symmetric or asymmetric couplings）. The mechanisms behind these differences are explained physically.     

Attractive target wave patterns in complex networks consisting of excitable nodes

This review describes the investigations of oscillatory complex networks consisting of excitable nodes,focusing on the target wave patterns or say the target wave attractors.A method of dominant phase advanced driving(DPAD) is introduced to reveal the dynamic structures in the networks supporting oscillations,such as the oscillation sources and the main excitation propagation paths from the sources to the whole networks.The target center nodes and their drivers are regarded as the key nodes which can completely determine the corresponding target wave patterns.Therefore,the center(say node A) and its driver(say node B) of a target wave can be used as a label,(A,B),of the given target pattern.The label can give a clue to conveniently retrieve,suppress,and control the target waves.Statistical investigations,both theoretically from the label analysis and numerically from direct simulations of network dynamics,show that there exist huge numbers of target wave attractors in excitable complex networks if the system size is large,and all these attractors can be labeled and easily controlled based on the information given by the labels.The possible applications of the physical ideas and the mathematical methods about multiplicity and labelability of attractors to memory problems of neural networks are briefly discussed.     

Investigation of strain effect on the hole mobility in GOI tri-gate pFETs including quantum confinement

The strain impact on hole mobility in the GOI tri-gate pFETs is investigated by simulating the strained Ge with quantum confinement from band structure to electro-static distribution as well as the effective mobility. Lattice mismatch strain induced by HfO2 warps and reshapes the valence subbands, and reduces the hole effective masses. The maximum value of hole density is observed near the top comers of the channel. The hole density is decreased by the lattice mismatch strain. The phonon scattering rate is degraded by strain, which results in higher hole mobility.     

Plasticity-induced characteristic changes of pattern dynamics and the related phase transitions in small-world neuronal networks

Phase transitions widely exist in nature and occur when some control parameters are changed. In neural systems, their macroscopic states are represented by the activity states of neuron populations, and phase transitions between different activity states are closely related to corresponding functions in the brain. In particular, phase transitions to some rhythmic synchronous firing states play significant roles on diverse brain functions and disfunctions, such as encoding rhythmical external stimuli, epileptic seizure, etc. However, in previous studies, phase transitions in neuronal networks are almost driven by network parameters （e.g., external stimuli）, and there has been no investigation about the transitions between typical activity states of neuronal networks in a self-organized way by applying plastic connection weights. In this paper, we discuss phase transitions in electrically coupled and lattice-based small-world neuronal networks （LBSW networks） under spike-timing-dependent plasticity （STDP）. By applying STDP on all electrical synapses, various known and novel phase transitions could emerge in LBSW networks, particularly, the phenomenon of self-organized phase transitions （SOPTs）： repeated transitions between synchronous and asynchronous firing states. We further explore the mechanics generating SOPTs on the basis of synaptic weight dynamics.