Polymer networks functionalized with low-valent phosphorus cations

In this work, we show that polymer networks composed of tertiary alkyl phosphines can be cleanly functionalized with phosphino-phosphonium or triphosphenium cations. Methods for functionalizing the polymers range from halide abstraction of commercially available reagents, to ligand exchange from simple to make reported compounds, and finally, macromolecular ligand design guided by observations made at the molecular level to accommodate the formation of kinetically favored triphosphenium cation functionalized networks. The synthesis, comprehensive characterization, and comparison of the new polymers to molecular analogues is outlined. It is shown the addition of the low valent phosphorus centers to the polymer network has the effect of tuning material physical properties.     

Computational-Based Approach for Predicting Porosity of Electrospun Nanofiber Mats Using Response Surface Methodology and Artificial Neural Network Methods

Comparative studies between response surface methodology (RSM) and artificial neural network (ANN) methods to find the effects of electrospinning parameters on the porosity of nanofiber mats is described. The four important electrospinning parameters studied included solution concentration (wt.%), applied voltage (kV), spinning distance (cm) and volume flow rate (mL/h). It was found that the applied voltage and solution concentration are the two critical parameters affecting the porosity of the nanofiber mats. The two approaches were compared for their modeling and optimization capabilities with the modeling capability of RSM showing superiority over ANN, having comparatively lower values of errors. The mean relative error for the RSM and ANN models were 1.97% and 2.62% and the root mean square errors (RMSE) were 1.50 and 1.95, respectively. The superiority of the RSM-based approach is due to its high prediction accuracy and the ability to compute the combined effects of the electrospinning factors on the porosity of the nanofiber mats.     

A method of segment protection based on p-cycle for dynamic multicast with limited-range wavelength converter in WDM network

In the optical multicast network, node and link failures have very important influence on the network survivability which may lead to multiple destinations cannot receive data. Based on the wavelength layered-graph method, a method of efficiency-score based on heuristic algorithm of pre-configured cycle (p-Cycle) based-segment protection (ESHS) for dynamic multicast with limited-range wavelength conversion was presented in this paper. By finding the multicast tree segment protection, the total available p-Cycles are constructed for the multicast. Then we calculate each p-Cycle efficiency-score, the highest efficient-score p-Cycle is selected as the multicast route protection p-Cycle. The simulation results show that the ESHS can get higher performance than the existing ESHT algorithm, in terms of multicast request blocking probability and wavelength utilization.     

Molecular structure and properties of click hydrogels with controlled dangling end defect

In this study, controlled amount of dangling ends is introduced to the two series of poly(ethylene glycol)‐based hydrogel networks with three and four crosslinking functionality by using click chemistry. The structure of the gels with regulated defect percentage is confirmed by comparing the results of low‐field NMR characterization and Monte Carlo simulation. The mechanical properties of these gels were characterized by tensile stress–strain behaviors of the gels, and the results are analyzed by Gent model and Mooney–Rivlin model. The shear modulus of the swollen gels is found to be dependent on the functionality of the network, and decreases with the defect percentage. Furthermore, the value of shear modulus well obeys the Phantom model for all the gels with varied percentage of the defects. The maximum extension ratio, obtained from the fitting of Gent model, is also found to be dependent on the functionality of the network, and does not change with the defect percentage, except at very high defect percentage. The value of the maximum extension ratio is between that predicted from Phantom model and the Affine model. This indicates that at the large deformation, the fluctuation of the crosslinking points is suppressed for some extend but still exists. Polymer volume fractions at various defect percentages obtained from prediction of Flory–Rehner model are found to be in well agreement with the swelling experiment. All these results indicate that click chemistry is a powerful method to regulate the network structure and mechanical properties of the gels. © 2016 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2016 , 54, 1227–1236     

Antimicrobial loading into and release from poly(ethylene glycol)/poly(acrylic acid) semi‐interpenetrating hydrogels

Electrostatic interactions within a semi‐interpenetrating network (semi‐IPN) gel can control the postsynthesis loading, long‐term retention, and subsequent release of small‐molecule cationic antibiotics. Here, electrostatic charge is introduced into an otherwise neutral gel [poly(ethylene glycol) (PEG)] by physically entrapping high‐molecular‐weight poly(acrylic acid) (PAA). The network structure is characterized by small‐angle neutron scattering. PEG/PAA semi‐IPN gels absorb over 40 times more antibiotic than PAA‐free PEG gels. Subsequent soaking in physiological buffer (pH 7.4; 0.15 M NaCl) releases the loaded antibiotics for periods as long as 30 days. The loaded gels elute antibiotics with diffusivities of 4.46 × 10^?8 cm²/s (amikacin) and 2.08 × 10^?8 cm²/s (colistin), which are two orders of magnitude less than those in pure PEG gels where diffusion is controlled purely by gel tortuosity. The release and hindered diffusion can be understood based on the partial shielding of the charged groups within the loaded gel, and they have a significant effect on the antimicrobial properties of these gels. © 2015 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2016 , 54, 64–72     

BP neural network recognition algorithm for scour monitoring of subsea pipelines based on active thermometry

Scour monitoring is an important concern for subsea pipeline systems. The active-thermometry-based scour monitoring is based on the difference of heat transfer properties between sediment and sand, recognizes the surrounding media though temperature changing patterns during heating and cooling processes, and hence detects the free spans. Based on the scour monitoring system, a two-layer BP neural network was employed to process the monitoring data and achieved media recognition. The network's inputs were normalized temperature time histories. The network's outputs denoted different media: sediment and water. To validate the method, three experiments were conducted; one was used for training the network and the other two for testing. Also, the effect of noise on the network's performance was studied through simulation. The results demonstrated the feasibility and robustness of the neural network.     

Network regularised Cox regression and multiplex network models to predict disease comorbidities and survival of cancer

In cancer genomics, gene expression levels provide important molecular signatures for all types of cancer, and this could be very useful for predicting the survival of cancer patients. However, the main challenge of gene expression data analysis is high dimensionality, and microarray is characterised by few number of samples with large number of genes. To overcome this problem, a variety of penalised Cox proportional hazard models have been proposed. We introduce a novel network regularised Cox proportional hazard model and a novel multiplex network model to measure the disease comorbidities and to predict survival of the cancer patient. Our methods are applied to analyse seven microarray cancer gene expression datasets: breast cancer, ovarian cancer, lung cancer, liver cancer, renal cancer and osteosarcoma. Firstly, we applied a principal component analysis to reduce the dimensionality of original gene expression data. Secondly, we applied a network regularised Cox regression model on the reduced gene expression datasets. By using normalised mutual information method and multiplex network model, we predict the comorbidities for the liver cancer based on the integration of diverse set of omics and clinical data, and we find the diseasome associations (disease–gene association) among different cancers based on the identified common significant genes. Finally, we evaluated the precision of the approach with respect to the accuracy of survival prediction using ROC curves. We report that colon cancer, liver cancer and renal cancer share the CXCL5 gene, and breast cancer, ovarian cancer and renal cancer share the CCND2 gene. Our methods are useful to predict survival of the patient and disease comorbidities more accurately and helpful for improvement of the care of patients with comorbidity. Software in Matlab and R is available on our GitHub page: https://github.com/ssnhcom/NetworkRegularisedCox.git.     

One‐dimensional CuII coordination polymers containing C2h‐symmetric 1,1′:4′,1′′‐terphenyl‐3,3′‐dicarboxylate linkers

Two new one‐dimensional Cu^II coordination polymers (CPs) containing the C_2h‐symmetric terphenyl‐based dicarboxylate linker 1,1′:4′,1′′‐terphenyl‐3,3′‐dicarboxylate (3,3′‐TPDC), namely catena‐poly[[bis(dimethylamine‐κN)copper(II)]‐μ‐1,1′:4′,1′′‐terphenyl‐3,3′‐dicarboxylato‐κ⁴O,O′:O′′:O′′′] monohydrate], {[Cu(C₂₀H₁₂O₄)(C₂H₇N)₂]·H₂O}_n, (I), and catena‐poly[[aquabis(dimethylamine‐κN)copper(II)]‐μ‐1,1′:4′,1′′‐terphenyl‐3,3′‐dicarboxylato‐κ²O³:O^3′] monohydrate], {[Cu(C₂₀H₁₂O₄)(C₂H₇N)₂(H₂O)]·H₂O}_n, (II), were both obtained from two different methods of preparation: one reaction was performed in the presence of 1,4‐diazabicyclo[2.2.2]octane (DABCO) as a potential pillar ligand and the other was carried out in the absence of the DABCO pillar. Both reactions afforded crystals of different colours, i.e. violet plates for (I) and blue needles for (II), both of which were analysed by X‐ray crystallography. The 3,3′‐TPDC bridging ligands coordinate the Cu^II ions in asymmetric chelating modes in (I) and in monodenate binding modes in (II), forming one‐dimensional chains in each case. Both coordination polymers contain two coordinated dimethylamine ligands in mutually trans positions, and there is an additional aqua ligand in (II). The solvent water molecules are involved in hydrogen bonds between the one‐dimensional coordination polymer chains, forming a two‐dimensional network in (I) and a three‐dimensional network in (II).     

Synthesis,structure and characterization of two new metal–organic coordination polymers based on the ligand 5‐iodobenzene‐1,3‐dicarboxylate

Two new coordination polymers (CPs) formed from 5‐iodobenzene‐1,3‐dicarboxylic acid (H₂iip) in the presence of the flexible 1,4‐bis(1H‐imidazol‐1‐yl)butane (bimb) auxiliary ligand, namely poly[[μ₂‐1,4‐bis(1H‐imidazol‐1‐yl)butane‐κ²N³:N^3′](μ₃‐5‐iodobenzene‐1,3‐dicarboxylato‐κ⁴O¹,O^1′:O³:O^3′)cobalt(II)], [Co(C₈H₃IO₄)(C₁₀H₁₄N₄)]_n or [Co(iip)(bimb)]_n, (1), and poly[[[μ₂‐1,4‐bis(1H‐imidazol‐1‐yl)butane‐κ²N³:N^3′](μ₂‐5‐iodobenzene‐1,3‐dicarboxylato‐κ²O¹:O³)zinc(II)] trihydrate], {[Zn(C₈H₃IO₄)(C₁₀H₁₄N₄)]·3H₂O}_n or {[Zn(iip)(bimb)]·3H₂O}_n, (2), were synthesized and characterized by FT–IR spectroscopy, thermogravimetric analysis (TGA), solid‐state UV–Vis spectroscopy, single‐crystal X‐ray diffraction analysis and powder X‐ray diffraction analysis (PXRD). The iip²⁻ ligand in (1) adopts the (κ¹,κ¹‐μ₂)(κ¹, κ¹‐μ₁)‐μ₃ coordination mode, linking adjacent secondary building units into a ladder‐like chain. These chains are further connected by the flexible bimb ligand in a trans–trans–trans conformation. As a result, a twofold three‐dimensional interpenetrating α‐Po network is formed. Complex (2) exhibits a two‐dimensional (4,4) topological network architecture in which the iip²⁻ ligand shows the (κ¹)(κ¹)‐μ₂ coordination mode. The solid‐state UV–Vis spectra of (1) and (2) were investigated, together with the fluorescence properties of (2) in the solid state.