Surface Decoration of Peptide Nanoparticles Enables Efficient Therapy toward Osteoporosis and Diabetes

A versatile surface decoration strategy to efficiently encapsulate water-soluble peptides is developed. By assembling peptide molecules into nanoparticles, diverse physiochemical properties of these compacted molecules are equalized to the surface properties of nanoparticles. Primarily driven by the generic electrostatic attractions, the surface of as-prepared peptide nanoparticles is decorated with charged amino acids-grafted poly(lactic-co-glycolic acid). This adsorbed polymer layer versatilely blocks the phase transfer of peptide nanoparticles by increasing their affinity to the dispersed phase solvent molecules. Attributed to the ultrahigh encapsulation efficiencies (> 96%), the peptide mass fraction inside the obtained microcomposites is higher than 48%. The plasma calcium level has been efficiently reduced for ≈3 weeks with only one single injection of salmon calcitonin-encapsulated microcomposite in osteoporotic rats. Similarly, one single injection of exenatide-encapsulated microcomposites efficiently controls the glycemic level in type 2 diabetic rats for up to 3 weeks. Overall, the developed versatile surface decoration strategy efficiently encapsulates peptides and improves their pharmacokinetic features, regardless of the molecular structure of peptide cargos.     

Inorganic Filler Enhanced Formation of Stable Inorganic-Rich Solid Electrolyte Interphase for High Performance Lithium Metal Batteries

Lithium metal (LM) is a promising anode material for next generation lithium ion based electrochemical energy storage devices. Critical issues of unstable solid electrolyte interphases (SEIs) and dendrite growth however still impede its practical applications. Herein, a composite gel polymer electrolyte (GPE), formed through in situ polymerization of pentaerythritol tetraacrylate with fumed silica fillers, is developed to achieve high performance lithium metal batteries (LMBs). As evidenced theoretically and experimentally, the presence of SiO₂ not only accelerates Li⁺ transport but also regulates Li⁺ solvation sheath structures, thus facilitating fast kinetics and formation of stable LiF-rich interphase and achieving uniform Li depositions to suppress Li dendrite growth. The composite GPE-based Li||Cu half-cells and Li||Li symmetrical cells display high Coulombic efficiency (CE) of 90.3% after 450 cycles and maintain stability over 960 h at 3 mA cm⁻² and 3 mAh cm⁻², respectively. In addition, Li||LiFePO₄ full-cells with a LM anode of limited Li supply of 4 mAh cm⁻² achieve capacity retention of 68.5% after 700 cycles at 0.5 C (1 C = 170 mA g⁻¹). Especially, when further applied in anode-free LMBs, the carbon cloth||LiFePO₄ full-cell exhibits excellent cycling stability with an average CE of 99.94% and capacity retention of 90.3% at the 160th cycle at 0.5 C.     

Joint multi-radio multi-channel assignment, scheduling, and routing in wireless mesh networks

The IEEE 802.11 DCF and EDCA mechanisms based on CSMA/CA are the most widely used random channel access mechanisms in wireless mesh networks (WMNs), but unfortunately these cannot effectively eliminate hidden terminal and exposed terminal problems in multi-hop scenarios. In this paper, we propose a set of efficient multi-radio multi-channel (MRMC) assignment, scheduling and routing protocols based on Latin squares for WMNs with MRMC communication capabilities, called “M4”, i.e., the Multiple access scheduling in Multi-radio Multi-channel Mesh networking. M4 uses nodal interference information to form cliques for inter-cluster and intra-cluster inWMNs, and then applies Latin squares to map the clique-based clustering structure to radios and channels for communication purposes. Then, M4 again applies Latin squares to schedule the channel access among nodes within each cluster in a collision-free manner. From a systematic view, we also design the corresponding MRMC routing to support M4 communication. Extensive simulation results show that M4 achieves much better performance than IEEE 802.11 standards and other channel access control protocols.     

硅纳米管的水热法合成与表征

采用水热法成功合成了新型的硅纳米管一维纳米材料,并采用透射电子显微镜、选区电子衍射分析、能量色散光谱及高分辨透射电子显微镜对合成的硅纳米管进行了表征．研究表明硅纳米管是一种多壁纳米管,为立方金刚石结构,生长顶端呈半圆形的闭合结构,由内部为数纳米的中空结构,中部为晶面间距约0.31nm的晶体硅壁层,最外层为低于2nm的无定形二氧化硅等三部分组成．     

A statistical self-organizing learning system for remote sensing classification

A new learning system called a statistical self-organizing learning system (SSOLS), combining functional-link neural networks, statistical hypothesis testing, and self-organization of a number of enhancement nodes, is introduced for remote sensing applications. Its structure consists of two stages, a mapping stage and a learning stage. The input training vectors are initially mapped to the enhancement vectors in the mapping stage by multiplying with a random matrix, followed by pointwise nonlinear transformations. Starting with only one enhancement node, the enhancement layer incrementally adds an extra node in each iteration. The optimum dimension of the enhancement layer is determined by using an efficient leave-one-out cross-validation method. In this way, the number of enhancement nodes is also learned automatically. A t-test algorithm can also be applied to the mapping stage to mitigate the effect of overfitting and to further reduce the number of enhancement nodes required, resulting in a more compact network. In the learning stage, both the input vectors and the enhancement vectors are fed into a least squares learning module to obtain the estimated output vectors. This is made possible by choosing the output layer linear. In addition, several SSOLSs can be trained independently in parallel to form a consensual SSOLS, whose final output is a linear combination of the outputs of each SSOLS module. The SSOLS is simple, fast to compute, and suitable for remote sensing applications, especially with hyperspectral image data of high dimensionality.     

Confinement of gold quantum dot arrays inside ordered mesoporous silica thin film

Periodic disposed quantum dot arrays are very useful for the large scale integration of single electron devices. Gold quantum dot arrays were self-assembled inside pore channels of ordered amino-functionalized mesoporous silica thin films, employing the neutralization reaction between chloroauric acid and amino groups. The diameters of quantum dots are controlled via changing the aperture of pore channels from 2.3 to 8.3 nm, which are characterized by HRTEM, SEM and FT-IR. UV-vis absorption spectra of gold nanoparticle/mesoporous silica composite thin films exhibit a blue shift and intensity drop of the absorption peak as the aperture of mesopores decreases,which represents the energy level change of quantum dot arrays due to the quantum size effect.     

Sensitivity analysis of ion implanted silicon wafers after rapid thermal annealing

In this study, we have investigated sensitivities of the ion implanted silicon wafers processed by rapid thermal annealing (RTA), which can reveal the variation of sheet resistance as a function of annealing temperature as well as implantation parameters. All the wafers were sequentially implanted by the arsenic or phosphorous implantations at 40, 80, and 100 keV with the dose level of 10¹⁴ to 2 × 10¹⁶ ions/cm². Rapid thermal annealing was carried out for 10 s by the infrared irradiation at a temperature between 850 and 1150°C in the nitrogen ambient. The activated wafer was characterized by the measurements of the sheet resistance and its uniformity mapping. The values of sensitivities are determined from the curve fitting of the experimental data to the fitting equation of correlation between the sheet resistance and process variables. From the sensitivity values and the deviation of sheet resistance, the optimum process conditions minimizing the effects of straggle in process parameters are obtained. As a result, a strong dependence of the sensitivity on the process variables, especially annealing temperatures and dose levels is also found. From the sensitivity analysis of the 10 s RTA process, the optimum values for the implant dose and annealing temperature are found to be in the range of 10¹⁶ ions/cm² and 1050-1100°C, respectively. The sensitivity analysis of sheet resistance will provide valuable data for accurate activation process, offering a guideline for dose monitoring and calibration of ion implantation process.     

Dominant mode characteristics of circular groove guide

Circular groove guide is a kind of waveguide for millimeter waves with low loss, large dimensions, and low dispersion. In this paper, the dominant mode characteristics of it is analysed. The technique that mode macthing method combines with point matching method is used to derive the Nth-order characteristic equation of the guide. The 1st order, 2nd order and 3rd order approximate curves that the normalized cutoff wavelength of circular groove guide varies with c/a are given. The attenuation curves are given at 1mm, 1.5mm and 3mm wavelength. The numerical results are in well agreement with the experimental results published.     

Tribotronic Phototransistor for Enhanced Photodetection and Hybrid Energy Harvesting

Tribotronics is a new field developed by coupling triboelectricity and semiconductor, which can drive triboelectric‐charge‐controlled optoelectronic devices by further introducing optoelectronics. In this paper, a tribotronic phototransistor (TPT) is proposed by coupling a field‐effect phototransistor and a triboelectric nanogenerator (TENG), in which the contact‐induced inner gate voltage by the mobile frictional layer is used for modulating the photodetection characteristics of the TPT. Based on the TPT, alternatively, a coupled energy‐harvester (CEH) is fabricated for simultaneously scavenging solar and wind energies, in which the output voltage on the external resistance from the wind driven TENG is used as the gate voltage of the TPT for enhancing the solar energy conversion. As the wind speed increases, the photovoltaic characteristics of the CEH including the short‐circuit current, open‐circuit voltage, and maximal output power have been greatly enhanced. This work has greatly expanded the functionality of tribotronics in photodetection and energy harvesting, and provided a potential solution for highly efficient harvesting and utilizing multitype energy.     

基于PSO-BP神经网络的无线传感器网络定位算法

针对无线传感器网络定位的基本功能问题。提出一种将PSO算法和BP神经网络相结合对RSSI在测距阶段测得的距离数据进行优化的算法。该算法将PSO算法作为BP神经网络的学习算法,缩短了BP神经网络的训练时间,并加快算法的收敛速度。通过仿真,定位精度较其他算法得到了明显提高,最高可达27.3%。