Preparation and characterization of Fe‐Tetranitro phthalocyanine/polyurethane blends

In this article, Fe‐Tetranitro phthalocyanine (Fe‐TNPc)/polyurethane (PU) blends were prepared by solution blending. The mechanical properties of the samples were studied by tensile tests. The results showed that the tensile strength and the elongation at break of the samples increased with increasing Fe‐TNPc content. The improved mechanical properties for the samples containing Fe‐TNPc was attributed to the increased microphase separation degree of PU, which was further investigated by dynamic mechanical analysis (DMA) and Fourier transform infrared analysis. The lower T_g of the soft segments and the higher T_g of the hard segments for the samples containing Fe‐TNPc indicated an increase of microphase separation degree of PU. The increased hydrogen bonded carbonyl groups in the samples with increasing Fe‐TNPc content also proved the conclusion. Quantitative evaluation of the interaction between Fe‐TNPc and PU was also investigated by analyzing the physical crosslinking density of the samples. The results indicated that the physical crosslinking density of the samples increased with increasing Fe‐TNPc content. The antibacterial properties of the samples were investigated. The results showed that the percentage bacterial inactivation toward S. aureus and E. coli of the samples were 98.9% and 90.9%, respectively, when Fe‐TNPc was added to 1%. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41284.     

The organization of biological sequences into constrained and unconstrained parts determines fundamental properties of genotype–phenotype maps

Biological information is stored in DNA, RNA and protein sequences, which can be understood as genotypes that are translated into phenotypes. The properties of genotype–phenotype (GP) maps have been studied in great detail for RNA secondary structure. These include a highly biased distribution of genotypes per phenotype, negative correlation of genotypic robustness and evolvability, positive correlation of phenotypic robustness and evolvability, shape-space covering, and a roughly logarithmic scaling of phenotypic robustness with phenotypic frequency. More recently similar properties have been discovered in other GP maps, suggesting that they may be fundamental to biological GP maps, in general, rather than specific to the RNA secondary structure map. Here we propose that the above properties arise from the fundamental organization of biological information into ‘constrained'' and ‘unconstrained'' sequences, in the broadest possible sense. As ‘constrained'' we describe sequences that affect the phenotype more immediately, and are therefore more sensitive to mutations, such as, e.g. protein-coding DNA or the stems in RNA secondary structure. ‘Unconstrained'' sequences, on the other hand, can mutate more freely without affecting the phenotype, such as, e.g. intronic or intergenic DNA or the loops in RNA secondary structure. To test our hypothesis we consider a highly simplified GP map that has genotypes with ‘coding'' and ‘non-coding'' parts. We term this the Fibonacci GP map, as it is equivalent to the Fibonacci code in information theory. Despite its simplicity the Fibonacci GP map exhibits all the above properties of much more complex and biologically realistic GP maps. These properties are therefore likely to be fundamental to many biological GP maps.     

Stimuli-Responsive Nanocomposite Hydrogels for Biomedical Applications

The complex tissue-specific physiology that is orchestrated from the nano- to the macroscale, in conjugation with the dynamic biophysical/biochemical stimuli underlying biological processes, has inspired the design of sophisticated hydrogels and nanoparticle systems exhibiting stimuli-responsive features. Recently, hydrogels and nanoparticles have been combined in advanced nanocomposite hybrid platforms expanding their range of biomedical applications. The ease and flexibility of attaining modular nanocomposite hydrogel constructs by selecting different classes of nanomaterials/hydrogels, or tuning nanoparticle-hydrogel physicochemical interactions widely expands the range of attainable properties to levels beyond those of traditional platforms. This review showcases the intrinsic ability of hybrid constructs to react to external or internal/physiological stimuli in the scope of developing sophisticated and intelligent systems with application-oriented features. Moreover, nanoparticle-hydrogel platforms are overviewed in the context of encoding stimuli-responsive cascades that recapitulate signaling interplays present in native biosystems. Collectively, recent breakthroughs in the design of stimuli-responsive nanocomposite hydrogels improve their potential for operating as advanced systems in different biomedical applications that benefit from tailored single or multi-responsiveness.     

Healing Pattern Analysis for Dental Implants Using the Mechano-Regulatory Tissue Differentiation Model

(1) Background: Our aim is to reveal the influence of the geometry designs on biophysical stimuli and healing patterns. The design guidelines for dental implants can then be provided. (2) Methods: A two-dimensional axisymmetric finite element model was developed based on mechano-regulatory algorithm. The history of tissue differentiation around eight selected implants can be predicted. The performance of the implants was evaluated by bone area (BA), bone-implant contact (BIC); (3) Results: The predicted healing patterns have very good agreement with the experimental observation. Many features observed in literature, such as soft tissues covering on the bone-implant interface; crestal bone loss; the location of bone resorption bumps, were reproduced by the model and explained by analyzing the solid and fluid biophysical stimuli and (4) Conclusions: The results suggested the suitable depth, the steeper slope of the upper flanks, and flat roots of healing chambers can improve the bone ingrowth and osseointegration. The mechanism related to solid and fluid biophysical stimuli were revealed. In addition, the model developed here is efficient, accurate and ready to extend to any geometry of dental implants. It has potential to be used as a clinical application for instant prediction/evaluation of the performance of dental implants.     

Sequence-Dependent Nanofiber Structures of Phenylalanine and Isoleucine Tripeptides

The molecular design of short peptides to achieve a tailor-made functional architecture has attracted attention during the past decade but remains challenging as a result of insufficient understanding of the relationship between peptide sequence and assembled supramolecular structures. We report a hybrid-resolution model to computationally explore the sequence–structure relationship of self-assembly for tripeptides containing only phenylalanine and isoleucine. We found that all these tripeptides have a tendency to assemble into nanofibers composed of laterally associated filaments. Molecular arrangements within the assemblies are diverse and vary depending on the sequences. This structural diversity originates from (1) distinct conformations of peptide building blocks that lead to different surface geometries of the filaments and (2) unique sidechain arrangements at the filament interfaces for each sequence. Many conformations are available for tripeptides in solution, but only an extended β-strand and another resembling a right-handed turn are observed in assemblies. It was found that the sequence dependence of these conformations and the packing of resulting filaments are determined by multiple competing noncovalent forces, with hydrophobic interactions involving Phe being particularly important. The sequence pattern for each type of assembly conformation and packing has been identified. These results highlight the importance of the interplay between conformation, molecular packing, and sequences for determining detailed nanostructures of peptides and provide a detailed insight to support a more precise design of peptide-based nanomaterials.     

湾图沟煤矿高强度采动巷道稳定性评价研究

针对高强度采动巷道围岩控制难题，从实验室岩样尺度和现场巷道尺度研究了湾图沟煤矿13405工作面回风平巷围岩稳定性特征。结合单轴压缩试验和声波测试分析了干燥、自然及饱和状态下3组岩样的力学行为差异特征。利用钻孔成像，分析了高强度采动影响巷道围岩裂隙发育分段特征。结果表明:干燥、自然及饱和状态下岩样的单轴抗压强度和弹性模量依次降低，水分的存在极大地降低了岩石的强度和刚度。实煤体段围岩仅在深度1 m范围内发现少量纵向裂隙。高静压段两帮维护效果较差，煤帮裂隙极为发育，存在高量值的离层。动压段巷道顶板完整性较好，两帮均发现较大离层，且超出了锚杆正常锚固范围，严重影响了巷道锚固结构的稳定性。     

Tuning effect of silicon substitution on magnetic and high frequency electromagnetic properties of R2Fe17 and their composites

In this work, we report the tuning effect of the Si substitution on the magnetic and high frequency electromagnetic properties of R₂Fe₁₇ compounds and their paraffin composites. It is found that the introduction of Si can remarkably improve the magnetic and electromagnetic properties of the R₂Fe₁₇ compounds, making the R₂Fe_17–xSi_x-paraffin composites excellent microwave absorption materials (MAMs). By introducing the Si element, their saturation magnetizations decrease slightly, while much higher Curie temperatures are obtained. Furthermore, better impedance match is reached due to the decrease of the high-frequency permittivity ε′ by about 40%–50%, which finally enhances the performance of the microwave absorption. The peak frequency (f_RL) of the reflection loss (RL) curve moves toward high frequency domain and the qualified bandwidth (QB, RL ≤ ?10 dB) increases remarkably. The maximum QB of 3.3 GHz (12.0–15.3 GHz) is obtained for the Sm_1.5Y_0.5Fe₁₅Si₂-paraffin composite (d = 1.0 mm) and the maximum RL of ?53.6 dB is achieved for Nd₂Fe₁₅Si₂-paraffin composite (d = 2.2 mm), both surpassing most of the reported MAMs. Additionally, a distinguished dielectric microwave absorption peak is observed, which further increases the QB in these composites.     

Sparse non-convex Lp regularization for cone-beam X-ray luminescence computed tomography

Cone-beam X-ray luminescence computed tomography (CB-XLCT) is an attractive hybrid imaging modality, and it has the potential of monitoring the metabolic processes of nanophosphors-based drugs in vivo. However, the XLCT imaging suffers from a severe ill-posed problem. In this work, a sparse nonconvex L_p (0?p?L₁ regularization. Further, an iteratively reweighted split augmented lagrangian shrinkage algorithm (IRW_SALSA-L_p) was proposed to efficiently solve the non-convex L_p (0?p?p-values (1/16, 1/8, 1/4, 3/8, 1/2, 5/8, 3/4, 7/8) in both 3D digital mouse experiments and in vivo experiments. The results demonstrate that the proposed non-convex methods outperform L₂ and L₁ regularization in accurately recovering sparse targets in CB-XLCT. And among all the non-convex p-values, our L_p(1/4?p?相似文献   

Prediction of process parameters of water-assisted injection molding based on inverse radial basis function neural network

Because of the introduction of new processing parameters in water-assisted injection molding (WAIM), processes control has become more difficult. First, design of experiment (DOE) was carried out by using optimized Latin hypercubes (Opt LHS). On the basis of this, computational fluid dynamics (CFD) method was used to simulate and calculate hollowed core ratios and wall thickness differences of cooling water pipe at different positions. Then inverse radial basis function (RBF) neural network model reflecting the fitting relationship between processing parameters and molding quality was established, and accuracy of the model was detected by cross validation. Finally, expected molding quality was applied to predict processing parameters, and the obtained molding quality under the predicted processing parameters was verified by computer aided engineering (CAE) simulation and experimental methods. The results showed that mean relative precisions of processing parameters such as melt temperature, delay time, short shot size, water pressure, and mold temperature for inverse RBF model were 98.6%, 93.6%, 98.5%, 93.9%, and 97.9%, respectively, which met the accuracy requirements. Furthermore, compared with expected values of hollowed core ratios and wall thickness differences, the average errors of CAE and experiment were 2.3% and 4.9%, respectively.